An imaging device and a system for the device

Abstract

Disclosed is an imaging device for acquiring an image of a gemstone sample comprising gemstone data indicative of an attribute of a gemstone sample, comprising a sample holder to support the gemstone sample; an electromagnetic radiation source to generate an excitation wave for transmission to / through the gemstone sample to produce a transmitted wave modified by the gemstone sample; an optical instrument positioned relative to and optically aligned to the sample holder and electromagnetic radiation source, to modulate the excitation wave to produce a modified excitation wave, or modulate the transmitted wave to produce a modified transmitted wave; a detector optically aligned to the sample holder, the electromagnetic radiation source, the optical instrument, to detect the transmitted wave and / or modified transmitted wave incident on the detector, to acquire the image of the gemstone sample. Further disclosed is a system for determining the gemstone parameter comprising the device, and methods of manufacture.

Description

AN IMAGING DEVICE AND A SYSTEM FOR THE DEVICETECHNICAL FIELD

[0001] Various aspects of this disclosure relate to an imaging device for acquiring at least one image of a gemstone sample comprising gemstone data indicative of an attribute of a gemstone sample, and a system for determining a gemstone parameter indicative of the attribute of the gemstone sample.BACKGROUND

[0002] The following discussion of the background is intended to facilitate an understanding of the present disclosure only. It should be appreciated that the discussion is not an acknowledgment or admission that any of the material referred to was published, known, or is part of the common general knowledge of the person skilled in the art in any jurisdiction as of the priority date of the disclosure.

[0003] Conventional gemstone identification methods involve the use of numerous handheld analytical tools such as a microscope, polariscope, dichroscope, UV-light, spectrograph and refractometer. A trained gemmologist capable of interpreting the results obtained using these tools is required for the identification of the gemstone.

[0004] Such conventional gemstone identification methods are time-consuming, expensive, require expert knowledge and numerous analytic tools. Further, as there is no objective and quantitative measure for determining a gemstone color, gemstone color determination is subjective due to the individual nature of human vision perception and inconsistencies of ambient conditions under which the gemstone is viewed. Often, the identification of a gemstone is inconsistent and / or inaccurate depending on the gemmologist’s data visualization and human perception of the data, which impacts the valuation of the gemstone.

[0005] In addition, traceability of a gemstone is paramount to provide greater transparency in the chain-of-custody practices, and the practice of tagging a gemstone to be uniquely tracked is a pre-requisite for gemstone trading. Laser inscription on a facet of the gemstone or tagging the gemstone with non-removeable DNA information are conventional methods which have been developed. However, said methods are not full-proof as laser inscriptions may be erased when the gemstone is cut, and tagging the gemstone with non-removable DNA information may damage the gemstone’s natural crystal lattice structure, thereby impacting the value of the gemstone.

[0006] Therefore, there is a need for an improved imaging device, and / or a system including the improved imaging device that seeks to address at least one of the aforementioned issues.SUMMARY

[0007] The disclosure was conceptualized to provide an improved imaging device for acquiring gemstone data indicative of an attribute of the gemstone sample, and a system comprising the improved imaging device for determining a gemstone parameter based on the gemstone data. To this end, the imaging device integrates the various gemstone analytical tools in a single device which further includes a detector for acquiring at least one image of the gemstone sample comprising the gemstone data required for gemstone identification, the gemstone data being indicative of the gemstone sample’s attributes such as its optical properties, geometric properties, color, clarity, origin and magnified details of inclusions and / or growth structures. The disclosure also comprises a system including the imaging device in data communication with a processor, which includes at least one machine learning algorithm for analyzing the gemstone data, and determining the gemstone parameter based on the gemstone data. The gemstone parameters may aid in the identification of the gemstone sample. In particular, the disclosure provides an objective and quantitative system for determining a gemstone color, which is device-independent, not subject to ambient conditions, and provides a platform for calculating a color difference between two gemstones, and for describing and comparing gemstone colors in a consistent manner. In addition, the disclosure provides means for determining a unique gemstone signature for tracking a gemstone, that preserves the original structure and value of the gemstone.

[0008] The improved imaging device and system thus provides a platform for the rapid, consistent and accurate identification of a gemstone sample, and obviates the need for the trained gemmologist, thereby providing a platform that is efficient and accessible to a wide variety of users.

[0009] According to a first aspect of the disclosure, an imaging device for acquiring at least one image of a gemstone sample, the at least one image comprising gemstone data indicative of an attribute of the gemstone sample, the imaging device comprising a sample holder configured to support the gemstone sample; an electromagnetic radiation source configured to generate an excitation wave for transmission to / through the gemstone sample to produce a transmitted wave modified by the gemstone sample; at least one optical instrument positioned relative to and optically aligned to the sample holder, and the electromagnetic radiation source,the at least one optical instrument configured to, modulate the excitation wave for transmission to / through the gemstone sample to produce a modified excitation wave, or modulate the transmitted wave to produce a modified transmitted wave; and a detector optically aligned to the sample holder, the electromagnetic radiation source, and the at least one optical instrument, wherein the detector is configured to detect the transmitted wave and / or the modified transmitted wave which is incident on the detector, to acquire the at least one image of the gemstone sample.

[0010] In various embodiments, the at least one optical instrument may comprise, a first optical instrument positioned between the electromagnetic radiation source and the sample holder, the first optical instrument configured to modulate the excitation wave for transmission through the gemstone sample to produce the modified excitation wave, wherein the first optical instrument comprises: a first polarizing filter, a grating assembly, and / or a prism assembly.

[0011] In various embodiments, the at least one optical instrument may further comprise a second optical instrument positioned between the sample holder and the detector, the second optical instrument configured to modulate the transmitted wave to produce the modified transmitted wave, wherein the second optical instrument comprises a second polarizing filter.

[0012] In various embodiments, the first polarizing filter and / or the second polarizing filter are configured to be rotatable along a horizontal and / or a vertical axis of the first and / or second polarizing filter.

[0013] In various embodiments, the imaging device may further comprise, providing, a calibrated refractometer scale optically aligned to the sample holder, the electromagnetic radiation source, the at least one optical instrument, and the detector, wherein the at least one optical instrument further comprises an optical plate or hemisphere or hemicylinder positioned adjacent to the sample holder, the optical plate or hemisphere or hemicylinder configured to modulate the excitation wave to produce the modified excitation wave; and to modulate the transmitted wave to produce the modified transmitted wave, and to project the modified transmitted wave onto the calibrated refractometer scale.

[0014] In various embodiments, the sample holder is configured to be rotatable along an abscissa, an ordinate and / or an applicate axis of the sample holder.

[0015] In various embodiments, the imaging device may further comprise, a sample chamber positioned adjacent to the sample holder, the sample chamber configured to contain an optical fluid, wherein the sample chamber is further configured to receive the sample holdersupporting the gemstone sample, such that the gemstone sample is suspended in the optical fluid contained therein.

[0016] In various embodiments, the excitation wave comprises a wavelength ranging between 100 to 3000 nm, optionally between 250 nm to 700 nm.

[0017] In various embodiments, the at least one image of the gemstone sample comprises at least one cross-sectional image of the gemstone sample, each cross-sectional image acquired along a longitudinal, sagittal and / or transverse plane of the gemstone sample.

[0018] According to a second aspect of the disclosure, there is provided a system for determining a gemstone parameter indicative of the attribute of the gemstone sample, the system comprising the imaging device of the first aspect; a processor in data communication with the imaging device, the processor configured to obtain, the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample; and determine, the gemstone parameter based on the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample.

[0019] In various embodiments, the processor comprises at least one machine learning algorithm, for determining the gemstone parameter, the machine learning algorithm optionally including a deep learning algorithm. In some embodiments, the deep learning algorithm comprises a convolutional neural network algorithm, a diffusion model and / or a vision transformer.

[0020] In various embodiments, the gemstone parameter may comprise an optical parameter indicative of an optical property of the gemstone sample, wherein the optical parameter comprises, a refractive index parameter indicative of a refraction index of the gemstone sample; a birefringence parameter indicative of a birefringence property related to a difference between the refractive index of at least two crystallographic axes of the gemstone sample; a pleochroism parameter indicative of a pleochroism property related to a color spectrum of the at least two crystallographic axes of the gemstone sample; an absorption parameter indicative of a characteristic absorption spectra related to a dispersion of the transmitted wave of the gemstone sample; a UV fluorescence and / or phosphorescence parameter indicative of a characteristic fluorescence and / or phosphorescence related to the transmitted wave of the gemstone sample.

[0021] In various embodiments, the gemstone parameter may further comprise a species parameter indicative of a class of the gemstone sample, wherein determining the species parameter is based on the determination of at least one of the refractive index parameter, thebirefringence parameter, the pleochroism parameter, the absorption parameter, the UV fluorescence and / or phosphorescence parameter, of the gemstone sample.

[0022] In various embodiments, wherein the gemstone parameter further comprises a geometric parameter indicative of a geometric property of the gemstone sample, wherein the geometric parameter comprises, a gemstone shape parameter indicative of a shape and dimension of the gemstone sample, a facet parameter indicative of a cut of at least one facet of the gemstone sample, wherein the processor is further configured to: construct, a gemstone sample image from the at least one image of the gemstone sample; compare, the gemstone sample image with each of a plurality of reference gemstone sample images, each reference gemstone sample image comprising a reference shape and dimension of the reference gemstone sample image, and further comprising a reference cut of at least one facet of the reference gemstone sample image; determine, the gemstone shape parameter based on the comparison of the gemstone sample image with each reference gemstone sample image comprising the reference shape and dimension of the reference gemstone sample image; determine, the facet parameter based on the comparison of the gemstone sample image with each reference gemstone sample image comprising the reference cut of the at least one facet of the reference gemstone sample image; and determine, the geometric parameter based on, at least one of the gemstone shape parameter and / or the facet parameter.

[0023] In various embodiments, the gemstone parameter may further comprise a clarity parameter indicative of a purity of the gemstone sample, wherein the clarity parameter comprises, an inclusion parameter indicative of one or more inclusion properties in the gemstone sample, the one or more inclusion properties comprising a position of the one or more inclusions, and / or a type of the one or more inclusions, in the gemstone sample; a growth structure parameter indicative of one or more growth structure properties in the gemstone sample, the one or more growth structure properties comprising a position of the one or more growth structures, and / or a mineralization pattern of the one or more growth structures, formed in the gemstone sample; wherein the processor is further configured to: compare, the gemstone sample image with each of the plurality of reference gemstone sample images, each reference gemstone sample image further comprising one or more reference inclusions in the reference gemstone sample image, and further comprising one or more reference growth structures in the reference gemstone sample image; determine, the inclusion parameter based on the comparison of the gemstone sample image, with each of the plurality of reference gemstone sample images comprising the one or more reference inclusions in the gemstone sample image, determine, thegrowth structure parameter based on the comparison of the gemstone sample image with each of the plurality of reference gemstone sample images comprising the one or more reference growth structures; and determine, the clarity parameter is based on, at least one of the inclusion parameter and / or the growth structure parameter.

[0024] In various embodiments, the gemstone parameter may further comprise an origin parameter indicative of a geological origin of the gemstone sample, wherein the processor is further configured to: compare, the inclusion parameter with each of a plurality of predetermined reference origin parameters, each predetermined reference origin parameter comprising a reference type of the one or more reference inclusions and / or a reference position of the one or more reference inclusions of a reference gemstone sample, and its relationship with a particular geographical location; and determine, the origin parameter based on the comparison of the inclusion parameter with each of the plurality of predetermined reference origin parameter.

[0025] In various embodiments, the gemstone parameter may further comprise a treatment parameter indicative of a treatment applied to the gemstone sample, wherein the processor is further configured to: compare, the inclusion parameter with each of a plurality of predetermined reference treatment parameters, each predetermined reference treatment parameter comprising a reference type of the one or more reference inclusions and / or a reference position of the one or more reference inclusions, and its relationship with a particular treatment applied to the reference gemstone sample; compare, the growth structure parameter with each of the plurality of predetermined treatment parameters, each predetermined reference treatment parameter further comprising a reference position of the one or more reference growth structures and / or a reference mineralization pattern of the one or more reference growth structures, and its relationship with the particular treatment applied to the reference gemstone sample; and determine, the treatment parameter based on the comparison of the inclusion parameter and / or the growth structure parameter with each of the plurality of predetermined reference treatment parameters.

[0026] In various embodiments, the gemstone parameter may comprise a color parameter indicative of a color class of the gemstone sample, wherein the processor is further configured to: determine, a representative color parameter indicative of a representative color coordinate assigned with respect to a uniform color space, compare, the representative color parameter with each reference color parameter among a plurality of reference color parameters, each reference color parameter indicative of a preassigned color coordinate corresponding to apredetermine color class of a respective one of the plurality of reference gemstone sample images, the preassigned color coordinate assigned with respect to the uniform color space, determine, a color score parameter indicative of a smallest color distance between the representative color parameter and at least one of the reference color parameters, compare, the color score parameter with a predetermined color tolerance threshold value indicative of a desired deviation between the representative color parameter and the at least one of the reference color parameters, and determine, the color parameter based on the comparison of the color score parameter with the predetermined color tolerance threshold value.

[0027] In various embodiments, the gemstone sample image comprises a plurality of pixels, and the processor may be configured to determine the representative color parameter by: determining, a pixel color parameter for each pixel of the plurality of pixels, the pixel color parameter indicative of a pixel color coordinate assigned with respect to the uniform color space; clustering, each pixel of the plurality of pixels into a pixel color cluster of a plurality of pixel color clusters, each pixel color cluster representative of a predetermined color cluster of the gemstone sample image, the clustering of each pixel based on the pixel color coordinate of a respective pixel; determining, for each pixel color cluster, a first color cluster parameter indicative of a centroid coordinate of a respective pixel color cluster, and a second color parameter indicative of a weighted average of each of the pixel color coordinate within the respective pixel color cluster, and determining, the representative color parameter based on the first color cluster parameter and the second color cluster parameter .

[0028] In various embodiments, wherein to determine the color parameter, the processor is further configured to, determine, whether the color score parameter is less than or equal to the predetermined color tolerance threshold value, and determine, the color parameter if it is determined that the color score parameter is less than or equal to the predetermined color tolerance threshold value.

[0029] In various embodiments, processor is further configured to determine, a unique gemstone signature for the gemstone sample, the unique gemstone signature comprising at least two gemstone parameters of the gemstone sample.

[0030] According to a third aspect of the disclosure, there is provided a method of manufacturing the imaging device of the first aspect, the method comprising, providing, a sample holder configured to support the gemstone sample; providing, an electromagnetic radiation source configured to generate an excitation wave for transmission to / through the gemstone sample to produce a transmitted wave modified by the gemstone sample; providing,at least one optical instrument positioned relative to and optically aligned to the sample holder, and the electromagnetic radiation source, the at least one optical instrument configured to modulate the excitation wave for transmission through the gemstone sample to produce a modified excitation wave, or modulate the transmitted wave to produce a modified transmitted wave; and providing, a detector optically aligned to the sample holder, the electromagnetic radiation source, and the at least one optical instrument, the detector configured to detect the transmitted wave and / or the modified transmitted wave, to acquire the at least one image of the gemstone sample.

[0031] According to a fourth aspect of the disclosure, there is provided a method for determining a gemstone parameter indicative of the attribute of the gemstone sample, comprising: providing, a processor in data communication with the imaging device of the first aspect, wherein the method further comprises, obtaining, the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample; determining, the gemstone parameter based on the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample.

[0032] In various embodiments, the processor comprises at least one machine learning algorithm, for determining the gemstone parameter, the machine learning algorithm optionally comprising a deep learning algorithm.

[0033] According to a fifth aspect of the disclosure, there is provided a computer readable medium comprising instructions, which when executed by the processor, causes the processor to perform the method of the fourth aspect.BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The disclosure will be better understood with reference to the detailed description when considered in conjunction with the non-limiting examples and the accompanying drawings, in which:- FIG. 1 shows an exemplary schematic illustration of an imaging device 100;- FIG. 2 shows an exemplary schematic illustration of a sample holder 102 of the imaging device 100;- FIG. 3 shows another exemplary schematic illustration of an imaging device 300;- FIG. 4 shows another exemplary schematic illustration of an imaging device 400;- FIG. 5 shows another exemplary schematic illustration of an imaging device 500, and the insets show examples of the third optical instrument 150 comprising (A) an optical plate 154; or (B) a hemicylinder 156; or (C) a hemisphere 158;- FIG. 6 shows an exemplary schematic illustration of a system 600 for determining a gemstone parameter 174 indicative of the attribute of the gemstone sample 104;- FIG. 7 shows (A) a schematic illustration of an exemplary uniform color space 700 for determining a gemstone parameter 174 comprising a color parameter 660 indicative of a color label of the gemstone sample 104; and (B) an exemplary graph 710 of the preassigned color coordinates corresponding to a predetermined color class of a respective reference gemstone sample image 634.- FIG. 8 shows an exemplary schematic illustration of various pixel color clusters 800 for determining a representative color parameter 662 indicative of a representative color coordinate of the gemstone sample 104, assigned with respect to a uniform color space in a (A) 3D format; and (B) 2D format;- FIG. 9 shows the comparison of the representative color parameter 662 of the gemstone sample image 632, with a reference color parameter 672, for determining a color score parameter 664;- FIG. 10 shows a flowchart of an exemplary method 1000 for manufacturing the imaging device; and- FIG. 11 shows a flowchart of an exemplary method 1100 for determining a gemstone parameter.DETAILED DESCRIPTION

[0035] The following detailed description refers to the accompanying drawings that show, by way of illustration, specific details and embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure. Other embodiments may be utilized and structural, and logical changes may be made without departing from the scope of the disclosure. The various embodiments are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments.

[0036] Features that are described in the context of an embodiment may correspondingly be applicable to the same or similar features in the other embodiments. Features that are described in the context of an embodiment may correspondingly be applicable to the other embodiments,even if not explicitly described in these other embodiments. Furthermore, additions and / or combinations and / or alternatives as described for a feature in the context of an embodiment may correspondingly be applicable to the same or similar feature in the other embodiments.

[0037] In the context of various embodiments, the articles “a”, “an” and “the” as used with regard to a feature or element include a reference to one or more of the features or elements. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0038] While such terms as "first," "second," etc., may be used to describe various elements, such elements are not be limited to the above terms. The above terms are used only to distinguish one element from another, and do not define corresponding elements, for example, an order and / or significance of the elements. Without departing a scope of rights of the specification, a first element may be referred to as a second element, and similarly, the second element may be referred to as the first element.

[0039] Throughout the description, the term, “image”, as used herein, may refer to an image, e.g. pictorial representation of a gemstone sample, which includes gemstone data indicative of an attribute of the gemstone sample. The image of the gemstone sample may be comprised in a transmitted wave and / or a modified transmitted wave, the modified transmitted wave being modulated by an optical instrument, and the transmitted wave and / or modified transmitted wave may be detected at a detector. In various embodiments, the term “image” may further include a cross-sectional image, e.g. pictorial representation of the gemstone sample.

[0040] Throughout the description, the term “attribute”, as used herein, may refer to a characteristic of the gemstone sample, comprised in the gemstone data. Non-limiting attributes of the gemstone sample may include a color, an optical property, a geometric property, a class, an inclusion or growth structure, a treatment condition applied to the gemstone sample, a geological origin.

[0041] Throughout the description, the term, “transmission to / through the gemstone sample”, as used herein, may refer to the transmission of the excitation wave to / through one or more facets, or one or more sides or points, of the gemstone sample. For example, the excitation wave may enter through one facet, and exit through another facet of the gemstone sample. In another example, the excitation wave may enter and exit through a same facet of the gemstone sample. Within the context of the disclosure, the excitation wave is transmitted through the gemstone sample and interacts with the gemstone sample to produce a transmitted wave.

[0042] Throughout the description, the term, “positioned relative to”, as used herein, may refer to the arrangement of the optical instrument with respect to the electromagnetic radiation source, the detector, the sample holder. In various embodiments, the optical instrument may be positioned in proximity to the sample holder, for example, adjacent to the sample holder. In various embodiments, the optical instrument may be positioned between the electromagnetic radiation source and sample holder, and / or between the sample holder and the detector. In some embodiments, there may not be intervening elements between the optical instrument and the electromagnetic radiation source, the detector, or the sample holder, so as to block the transmission path of the excitation wave, the modified excitation wave, the transmitted wave, and / or the modified transmitted wave. In some embodiments, the optical instrument may be positioned relative to the sample holder such that it may be in direct contact with the sample holder and / or the gemstone sample. In some other embodiments, the optical instrument may be positioned relative to the sample holder such that it may not be in direct contact with the sample holder and / or the gemstone sample.

[0043] Throughout the description, the term “gemstone parameter”, as used herein, may refer to a value, or a range of values, the value comprising at least one alphanumeric digit. The gemstone parameter may be determined based on the gemstone data comprised in at least one image of the gemstone sample, which may be comprised in the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave and / or the first, second, third modified transmitted wave. In some embodiments, the gemstone parameter may comprise an integer, or may comprise a fractional number, for example, a refractive index. In some other embodiments, the gemstone parameter may comprise an alphabet or a string of alphabets, for example, a color class, a treatment condition applied to the gemstone sample.

[0044] According to various embodiments, a circuit may include analog circuits or components, digital circuits or components, or hybrid circuits or components. Any other kind of implementation of the respective functions which will be described in more detail below may also be understood as a "circuit" in accordance with an alternative embodiment. A digital circuit may be understood as any kind of a logic implementing entity, which may be special purpose circuitry or a processor executing software stored in a memory, firmware, or any combination thereof. Thus, in various embodiments, a "circuit" may be a digital circuit, e.g. a hard-wired logic circuit or a programmable logic circuit such as a programmable processor, e.g. a microprocessor (e.g. a Complex Instruction Set Computer (CISC) processor or a Reduced Instruction Set Computer (RISC) processor). A "circuit" may also include a processor or acontroller for executing software, e.g. any kind of computer program, e.g. a computer program using a virtual machine code such as e.g. Java. In various embodiments, the processor may comprise various units, each in data communication with each other. The processor may include (i.) a micro-controller unit comprising firmware stored therein for executing instructions for controlling the imaging device; (ii.) a central processing unit comprising software and a user-interface for controlling the various imaging modes of the imaging device to obtain gemstone data; and (iii.) a server unit, e.g. cloud infrastructure for storing gemstone data, processing the gemstone data to determine the gemstone parameter and / or training the machine-learning algorithms for determining the gemstone parameter. In some embodiments, the central processing unit may be further configured to process the gemstone data to determine the gemstone parameter and / or train the machine-learning algorithms for determining the gemstone parameter.

[0045] FIG. 1 shows an exemplary schematic illustration of an imaging device 100. FIG. 2 shows an exemplary schematic illustration of a sample holder 102 of the imaging device 100.

[0046] In various embodiments, the imaging device 100 may be in data communication with a processor 170, e.g. a controller for controlling, e.g. activating or deactivating, the various imaging modes of the imaging device 100, and for obtaining gemstone data 172 indicative of an attribute of the gemstone sample 104, as will be explained below.

[0047] Referring to FIG. 1, the imaging device 100 includes a sample holder 102 configured to support a gemstone sample 104. The sample holder 102 may comprise a platform configured to hold the gemstone sample 104, for example, via one or more claws (not shown) configured to receive and grip the gemstone sample 104. In some embodiments, as shown in FIG. 2, the sample holder 102 may comprise an end effector having a tweezer-like manipulator 102b having one or more claws (not shown) for gripping the gemstone sample 104. In some other embodiments, the sample holder 102 may be a pneumatic micro suction-cup which applies a pneumatic suction force for gripping the gemstone sample 104. In yet some other embodiments, an adhesive substance may be applied to secure, e.g. bond the gemstone sample 104 to the sample holder 102. It is further contemplated that the sample holder 102 may comprise any of the aforementioned combinations. The sample holder 102 as shown in FIGS. 1 and 2 may be manually or robotically, e.g. via the processor 170, attached to the gemstone sample 104, and may be configured to suspend the gemstone sample 104 in air.

[0048] The sample holder 102 may be configured to be rotatable along at least one of a vertical axis DI, i.e. y-axis or ordinate axis; a horizontal axis D2, i.e. x-axis or abscissa axis; arotational axis D3, i.e. z-axis or applicate axis. The horizontal axis D2 may be perpendicular to the vertical axis DI, and the rotational axis D3 may be perpendicular to the horizontal axis D2 and the vertical axis DI. Accordingly, the sample holder 102 may be configured to orientate the gemstone sample 104 in numerous degrees of freedom. The rotation of the sample holder 102 may be controlled by the processor 170, for example, the processor 170 may control the one or more robotic arms 102a of the sample holder 102 to rotate about the vertical axis DI, the horizontal axis D2 and / or the rotational axis D3 of the sample holder 102 (see FIG. 2).

[0049] In various embodiments, the imaging device 100 may further include a sample chamber 106 positioned adjacent to the sample holder 102, and configured to receive the sample holder 102. The sample chamber 106 may comprise a receptacle configured to contain an optical fluid. The optical fluid may have a refractive index ranging from 0.5 to 2.0, optionally 1.5 to 2.0. In various embodiments, the optical fluid may comprise a high refractive index optical fluid such as but not limited to Diiodomethane (CH2I2), having a refractive index of 1.7, which may be similar to the refractive index of the gemstone sample 104. In various embodiments, the sample holder 102 maybe positioned within, e.g. inside, the sample chamber 106 such that the gemstone sample 104 is suspended in the optical fluid. The optical fluid may reduce or prevent light refraction at the border between the gemstone sample 104 and air, i.e. sample-air border, thereby improving the quality of the image acquired by the detector 120.

[0050] The imaging device 100 further includes an electromagnetic radiation source 110 in optical alignment to the sample holder 102, and configured to generate an excitation wave 112 for transmission to / through the gemstone sample 104. As shown in FIG. 1, the electromagnetic radiation source 110 may be positioned within an illumination chamber 108, which encases, and surrounds the sample holder 102, and optionally, the sample chamber 106, so as to provide an enclosed area with a controlling lighting environment.

[0051] The excitation wave 112 may have a wavelength ranging from 100 nm to 3000 nm. In various embodiments, the excitation wave 112 may be in the visible light spectrum and may have a wavelength ranging from 400 nm to 700 nm. In some embodiments, the excitation wave 112 may be in the short-wave ultraviolet (UV) spectrum and may have a wavelength ranging from 180 nm to 250 nm. In some other embodiments, the excitation wave 112 may be in the long-wave UV spectrum and may have a wavelength ranging from 300 nm to 400 nm. In some other embodiments, the excitation wave 112 may be in the near infra-red spectrum and may have a wavelength ranging from 800 nm to 2500 nm. The electromagnetic radiation source 110may be configured to generate the excitation wave 112 having varying wavelength ranges depending on an imaging mode that the imaging device 100 may be operating in.

[0052] The excitation wave 112 may be transmitted such that it passes through one or more facets of the gemstone sample 104. As the excitation wave 112 is transmitted therethrough, the excitation wave 112 may interact with the gemstone sample 104 to produce a first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, which has been modified by the gemstone sample 104.

[0053] The imaging device 100 further includes a detector 120 in optical alignment with the electromagnetic radiation source 110 and the sample holder 102, and configured to acquire at least one image of the gemstone sample 104. The at least one image of the gemstone sample 104 may be comprised in a transmitted wave 122, 124, 126, 128, 129, 141, 143, 152. In some embodiments, the detector 120 may be configured to acquire at least one image of the gemstone sample 104 comprised in a modified transmitted wave 142, 144, 154 (see FIGS. 4 and 5). The at least one image of the gemstone sample 104 may comprise gemstone data 172 indicative of an attribute of the gemstone sample 104. The detector 120 may include an imaging sensor, for example, a high-resolution camera, and may further include a zero-angular field-of-view lens. It is contemplated that the detector 120 may include any suitable lens configuration for acquiring the at least one image of the gemstone sample 104.

[0054] In various embodiments, the at least one image may comprise at least one cross- sectional image of the gemstone sample 104. In other words, the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, and / or the first, second, third modified transmitted wave 142, 144, 154 may comprise a pictorial representation of a cross-section of the gemstone sample 104, each cross-sectional image comprising gemstone data 172 indicative of an attribute of the gemstone sample 104. Each cross-section of the gemstone sample 104 may comprise a 2D image, or may comprise a 3D image. In some embodiments, each cross-sectional image may be acquired along a transverse, e.g. horizontal plane of the gemstone sample 104. For example, each cross-sectional image along the transverse plane may be acquired from a top to a bottom, of the gemstone sample 104. In some other embodiments, each cross-sectional image may be acquired along a longitudinal, e.g. vertical plane of the gemstone sample 104, for example, from the left to the right of the gemstone sample 104. In yet some other embodiments, each cross-sectional image may be acquired along a sagittal plane of the gemstone sample 104, for example, from the front to the back of the gemstone sample 104. Each cross-sectional image along the aforementionedplanes may be acquired at a pre-defined interval, for example, a desired pre-defined distance, along said plane. The pre -defined interval may be determined by a user, for example, via a user interface of the processor 170.

[0055] In various embodiments of the imaging device 100 as shown in FIGS. 1 and 2, the imaging device 100 may be particularly suitable for operating as a light spectroscope, for acquiring at least one image of the gemstone sample 104 comprising gemstone data 172 of a color of the gemstone sample 104, which may be comprised in a first transmitted wave 122. In various embodiments, the color of the gemstone sample 104, gemstone data 172 of which is comprised in the first transmitted wave 122, may be imaged when the electromagnetic radiation source 110 outputs the excitation wave 112 having a wavelength ranging from 400 nm to 700 nm, i.e. visible light spectrum.

[0056] In various other embodiments of the imaging device 100 as shown in FIGS. 1 and 2, the imaging device 100 may further include a magnification lens (not shown), and the excitation wave 112 may have a wavelength ranging from 400 nm to 700 nm, i.e. visible light spectrum. The magnification lens may have a magnification value ranging from 0.5X to 100X, optionally ranging from 10X to 50X. In this embodiment, the imaging device 100 may be particularly suitable for acquiring images of the gemstone sample 104 comprising gemstone data 172 indicative of one or more inclusion properties and / or one or more growth structure properties of the gemstone sample 104, which may be comprised in a second transmitted wave 124. The inclusion property may include a position of one or more inclusion and / or a type of the one or more inclusion in the gemstone sample 104. The growth structure property may include a position of one or more growth structures and / or a mineralization pattern of the one or more growth structures in the gemstone sample 104.

[0057] In yet various other embodiments of the imaging device 100 as shown in FIGS. 1 and 2, the electromagnetic radiation source 110 may be configured to generate the excitation wave 112 in the short-wave UV spectrum, i.e. wavelength ranging from 180 nm to 250 nm, or in the long-wave UV spectrum, i.e. wavelength ranging from 300 nm to 400 nm. In this embodiment, the imaging device 100 may be particularly suitable for fluorescence spectroscopy, to acquire images of the gemstone sample 104 comprising gemstone data 172 indicative of a UV florescence and / or a phosphorescence of the gemstone sample 104, which may be comprised in a third transmitted wave 126. The UV florescence and / or phosphorescence may be indicative of a characteristic fluorescence and / or phosphorescence related to the third transmitted wave 126 of the gemstone sample 104.

[0058] FIG. 3 shows another exemplary schematic illustration of an imaging device 300. The imaging device 300 may be based on imaging device 100 discussed with reference to FIGS. 1 and 2. In FIG. 3, the sample chamber 106 and illumination chamber 108 are not shown for clarity.

[0059] Referring to FIG. 3, imaging device 300 may further include a first optical instrument 130 positioned between the electromagnetic radiation source 110 and the sample holder 102, the first optical instrument 130 configured to modulate the excitation wave 112 to produce a modified excitation wave 132, 134. In various embodiments, the first optical instrument 130 may be configured to be rotatable along a horizontal axis , i.e. x-axis and / or a vertical axis y, i.e. y-axis of the first optical instrument 130. The modified excitation wave 132, 134 may be transmitted to / through the gemstone sample 104, and the detector 120 may acquire the image of the gemstone sample 104 which may be comprised in the fourth and fifth transmitted wave 128, 129, which is based on the interaction of the modified excitation wave 132 and the gemstone sample 104. In various embodiments, the first optical instrument 130 may comprise, a first polarizing filter, a grating assembly and / or a prism assembly.

[0060] In various embodiments, the first optical instrument 130 may comprise a first polarizing filter, and the electromagnetic radiation source 110 may be configured to generate the excitation wave 112 having a wavelength ranging from 400 nm to 700 nm, i.e. visible light spectrum. The polarizing filter may interact with the excitation wave 112 to produce a first modified excitation wave 132 for transmission to / through the gemstone sample 104. In this embodiment, the imaging device 300 is particularly suitable for operating as a pleochroism spectroscope, to acquire images of the gemstone sample 104, comprising gemstone data 172 indicative of a pleochroism property of the gemstone sample 104, which may be comprised in a fourth transmitted wave 128. The pleochroism property may be related to a color spectrum of at least two crystallographic axes of the gemstone sample 104.

[0061] In various other embodiments, the first optical instrument 130 may comprise a prism assembly or a grating assembly, and the electromagnetic radiation source 110 may be configured to generate the excitation wave 112 having a wavelength ranging from 400 nm to 700 nm, i.e. visible light spectrum. The polarizing filter may interact with the excitation wave 112 to produce a second modified excitation wave 134 for transmission to / through the gemstone sample 104. In this embodiment, the imaging device 300 is particularly suitable for operating as an absorption spectroscope, to acquire images of the gemstone sample 104 which may be comprised in a fifth transmitted wave 129. The images of the gemstone sample 104may comprise gemstone data 172 indicative of a characteristic absorption spectrum related to a dispersion of the fifth transmitted wave 129 as it is transmitted through the gemstone sample 104.[00621 FIG. 4 shows another exemplary schematic illustration of an imaging device 400. The imaging device 400 may be based on imaging device 300 discussed with reference to FIG. 3. In FIG. 4, the sample chamber 106 and illumination chamber 108 are not shown for clarity. [00631 Referring to FIG. 4, the imaging device 400 may further include a second optical instrument 140 positioned between the sample holder 102 and the detector 120, the second optical instrument 140 configured to modulate a sixth and seventh transmitted wave 141, 143 to produce a first and second modified transmitted wave 142, 144. In various embodiments, the second optical instrument 140 may be configured to be rotatable along a horizontal axis r, i.e. x-axis and / or a vertical axis y, i.e. y-axis of the second optical instrument 140. The second optical instalment 140 may comprise a second polarizing filter, and the excitation wave 112 may have a wavelength ranging from 400 nm to 700 nm, i.e. visible light spectrum. In the embodiment as shown in FIG. 4, the first optical instrument 130 may comprise the first polarizing filter, and the excitation wave 112 may first be modulated by a first optical instrument 130 to produce the first modified excitation wave 132 which is transmitted through the gemstone sample 104. The gemstone sample 104 modifies the first modified excitation wave 132 to produce a sixth and seventh transmitted wave 141, 143.

[0064] In various embodiments of the imaging device 400 as shown in FIG. 4, the imaging device 400 may be particularly suitable for operating as a spectrometer for determining geometric properties of the gemstone sample 104, and the second optical instrument 140 may modulate the sixth transmission wave 141 to provide a first modified transmitted wave 142. The detector 120 may therefore acquire images of the gemstone sample 104 comprising gemstone data 172 indicative of a geometric property of the gemstone sample 104, which may be comprised in the first modified transmitted wave 142.

[0065] In various other embodiments of the imaging device 400 as shown in FIG. 4, the imaging device 400 may be particularly suitable for birefringence spectroscopy, and the second optical instrument 140 may modulate a seventh transmission wave 143 to provide a second modified transmitted wave 144. The detector 120 may therefore acquire images of the gemstone sample 104 comprising gemstone data 172 indicative of a birefringence property of the gemstone sample 104, which may be comprised in a second modified transmitted wave 144. The birefringence property may comprise a single refractive property, a double refractiveproperty and / or a poly-crystalline property of the gemstone sample 104. The birefringence property may be related to a difference between a refractive index of at least two crystallographic axes of the gemstone sample 104.

[0066] FIG. 5 shows another exemplary schematic illustration of an imaging device 500, and the insets show examples of the third optical instrument 150 comprising (A) an optical plate 154; or (B) a hemicylinder 156; or (C) a hemisphere 158. The imaging device 500 may be based on imaging device 100 discussed with reference to FIGS 1 and 2. In FIG. 5, the sample chamber 106 and illumination chamber 108 are not shown for clarity.

[0067] Referring to FIG. 5, the imaging device 500 may include a third optical instrument 150 positioned adjacent to the sample holder 102. In some embodiments, the third optical instrument 150 may be further positioned adjacent, for example, perpendicular to at least one facet of the gemstone sample 104 and is in direct contact with the gemstone sample 104. The third optical instrument 150 may comprise any one of an optical plate 154 (see FIG. 5A); a hemicylinder 156 (see FIG. 5B); or a hemisphere 158 (see FIG. 5C). The imaging device 500 may further include a calibrated refractometer scale (not shown) optically aligned to the sample holder 102, the electromagnetic radiation source 110, the third optical instrument 150 and the detector 120. In the embodiment as shown in FIG. 5, the imaging device 500 may be particularly suitable for refraction spectroscopy, i.e. operate as a refractometer to acquire gemstone data 172 indicative of a refractive index of the gemstone sample 104.

[0068] When the excitation wave 112 comprises, a wavelength ranging from 400 nm to 700 nm, i.e. visible light spectrum, the third optical plate 150 may be configured to modulate the excitation wave 112 to produce a third modified excitation wave 136 for transmission through the gemstone sample 104, and may be further configured to modulate an eighth transmitted wave 152, which is produced based on the interaction between the gemstone sample 104 and the third modified excitation wave 136, to produce a third modified transmission wave 154. The detector 120 may therefore acquire images of the gemstone sample 104, comprising gemstone data 172 indicative of a refractive index of the gemstone sample 104, which may be comprised in the third modified transmission wave 154.

[0069] In various embodiments, a layer of contact liquid may be provided to create an optical contact between the third optical instrument 150, e.g. hemicylinder 156 (see FIG. 5B) and the gemstone sample 104, and to pre vent air from being trapped between a facet of the gemstone sample 104 and the third optical instrument 150. Trapped air at the interface between the facet of the gemstone sample 104 and the third optical instrument 150, may affect the totalinternal reflection phenomenon, and affect the accuracy of the gemstone data 172 indicative of the refractive index of the gemstone sample 104. As the contact liquid also has a refractive index, the provision of the optical contact as a “thin film”, for example having a thickness of 0.1 mm to 1 mm is preferred so as to prevent the gemstone sample 104 from floating on a surface of the contact liquid, as this may cause refraction of the eight transmitted wave 152 within the liquid and affect the accuracy of the gemstone data 172 indicative of the refractive index of the gemstone sample 104 comprised in the third modified transmitted wave 154.

[0070] In various embodiments, each of the first, second and third optical instruments 130, 140, 150 may be in data communication, for example, via wired or wireless means, to the processor 170, and the various imaging modes may be controlled by the processor 170. In some embodiments, the various imaging modes may be activated or deactivated based on inputs provided by a memory 180, the processor 170 is in data communication with, for example, based on the execution of instructions stored in the memory 180. In some other embodiments, the imaging mode may be based on a user-selected input provided using a user interface of the processor 170. For example, the processor 170 may be configured to activate a refraction spectroscopy mode, to acquire gemstone data 172 indicative of a refractive index of the gemstone sample 104. The processor 170 may therefore be configured to activate and position the third optical instrument 150 such that it is optically aligned and adjacent to the sample holder 102 and / or the gemstone sample 104.

[0071] The imaging device 100, 300, 400, 500 discussed with reference to FIGS. 1 to 5 may therefore provide an automated device which integrates various optical instruments such as but not limited to the first and second polarizing filters, prism or grating assembly, optical plate, high magnification lenses and a sample holder 102 having a tweezer-like manipulator 102b to provide numerous degrees of freedom. The device may be able to acquire images of the gemstone sample 104 comprising gemstone data 172 indicative of various gemstone sample 104 attributes, which may be comprised in the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, and / or the first, second, third modified transmitted wave 142, 144, 154.

[0072] FIG. 6 shows an exemplary schematic illustration of a system 600 for determining a gemstone parameter 174 indicative of the attribute of the gemstone sample 104, according to another aspect of the disclosure. The system 600 may include the imaging device 100, 300, 400, 500 discussed with reference to FIGS. 1 to 5, and may comprise the processor 170 in data communication with the imaging device 100, 300, 400, 500.

[0073] In various embodiments, the processor 170 may be in data communication with the imaging device 100, 300, 400, 500 via wireless means, for example, according to one or more pre-defined wireless protocols. Examples of the pre-defined wireless communication protocols include: global system for mobile communication (GSM), enhanced data GSM environment (EDGE), wideband code division multiple access (WCDMA), code division multiple access (CDMA), time division multiple access (TDMA), wireless fidelity (Wi-Fi), voice over Internet protocol (VoIP), worldwide interoperability for microwave access (Wi-MAX), Wi-Fi direct (WFD), an ultra-wideband (UWB), infrared data association (IrDA), Bluetooth, ZigBee, SigFox, LPWan, LoRaWan, GPRS, 3G, 4G, LTE, and 5G communication systems. Alternatively, the processor 170 may be in data communication with the imaging device 100, 300, 400, 500 via wired means.

[0074] In system 600, the processor 170 may be configured to: obtain, the at least one image the of the gemstone sample 104 comprising gemstone data 172 indicative of various attributes of the gemstone sample 104; and determine, a gemstone parameter 174 based on the at least one image comprising gemstone data 172 indicative of various attributes of the gemstone sample 104. The image of the gemstone sample 104 may be comprised in the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, and / or the first, second, third modified transmitted wave 142, 144, 154, which may be detected when the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, and / or the first, second, third modified transmitted wave 142, 144, 154 is incident on the detector 120.

[0075] In various embodiments, the processor 170 may comprise at least one machine learning algorithm for determining the gemstone parameter 174. In some embodiments, the machine learning algorithm may comprise a supervised or semi-supervised or unsupervised machine learning algorithm for determining the gemstone parameter 174. In some embodiment, the machine learning algorithm may comprise a deep learning algorithm. In some embodiments, the deep learning algorithm may comprise a convolutional neural network algorithm, a diffusion model and / or a vision transformer.

[0076] As shown in FIG. 6, the system 600 may further comprise a memory 180 in data communication with the processor 170 via wireless or wired means. The memory 180 may store one or more reference gemstone sample images 634; and / or one or more reference parameters, for example, a plurality of reference color parameters 672, and may transmit thereference gemstone sample images 634 and / or reference parameters to the processor 170, for the identification of the gemstone sample 104.

[0077] Referring to FIG. 6, the gemstone parameter 174 may comprise an optical parameter 610 indicative of an optical property of the gemstone sample 104. In various embodiments, the optical parameter 610 may comprise at least one of a UV fluorescence and / or phosphorescence parameter 612, a pleochroism parameter 614, an absorption parameter 615, a birefringence parameter 616, a refractive index parameter 618. The various optical parameters 610 may aid in the identification of the gemstone sample 104, and the determination of a unique gemstone signature parameter 690 for the gemstone sample 104.

[0078] In various embodiments, the optical parameter 610 may comprise, a UV fluorescence and / or phosphorescence parameter 612 indicative of a characteristic fluorescence and / or phosphorescence related to the third transmitted wave 126 of the gemstone sample 104. In other words, the UV fluorescence and / or phosphorescence parameter 612 may be determined based on the gemstone data 172 comprised in the third transmitted wave 126 (see FIG. 1). Some gemstones may be inert and may not react to an excitation wave 112 in the short-wave UV spectrum or the long-wave UV spectrum. However, a gemstone sample 104 having a characteristic reaction to said excitation wave 112, may provide a useful indicator for the gemstone sample 104 identification. In some embodiments, the UV fluorescence and / or phosphorescence parameter 612 may be compared against one or more reference UV fluorescence and / or phosphorescence parameters, which may be stored in the memory 180, to aid in the identification of the gemstone sample 104.

[0079] In various embodiments, the optical parameter 610 may comprise, a pleochroism parameter 614 indicative of a pleochroism property related to a color spectrum of at least two crystallographic axes of the gemstone sample 104. The pleochroism parameter 614 may be determined based on gemstone data 172 comprised in the fourth transmitted wave 128 (see FIG. 3), which may show various colors of the gemstone sample 104 when viewed along different crystallographic axes. For example, the pleochroism parameter 614 may be related to the absorption of specific wavelengths of the first modified excitation wave 132. In some embodiments, the pleochroism parameter 614 may be compared against one or more reference pleochroism values, which may be stored in the memory 180, for the identification of the gemstone sample 104.

[0080] In various embodiments, the optical parameter 610 may comprise, an absorption parameter 615 indicative of a characteristic absorption spectra related to a dispersion of thefifth transmitted wave 129 of the gemstone sample 104. That is, the absorption parameter 615 may be determined based on gemstone data 172 comprised in the fifth transmitted wave 129 (see FIG. 3), which may show the dispersion of the second modified excitation wave 134 into its component color. The characteristic absorption spectra may be dependent on the crystal lattice of the gemstone sample 104 and / or the presence of inclusions or growth structure, e.g. impurities within the crystal lattice. In some embodiments, the absorption parameter 615 may be compared against one or more reference absorption parameters, which may be stored in the memory 180, for the identification of the gemstone sample 104.

[0081] In various embodiments, the optical parameter 610 may comprise, a birefringence parameter 616 indicative of a birefringence property related to a difference between a refractive index of at least two crystallographic axes of the gemstone sample 104. The birefringence parameter 616 may be determined based on the gemstone data 172 comprised in the second modified transmitted wave 144 (see FIG. 4), and may be determined based on the difference in the refractive index between two crystallographic directions of the gemstone sample 104. For example, the birefringence parameter 616 may be present in anisotropic gemstone sample 104 lattices which show different optical properties along different crystallographic axes, and may in particular be present in gemstone sample 104 with hexagonal or trigonal crystal lattices. In some embodiments, the birefringence parameter 616 may be compared against one or more reference birefringence parameters, which may be stored in the memory 180, for the identification of the gemstone sample 104.

[0082] In various embodiments, the optical parameter 610 may comprise, a refractive index parameter 618 indicative of a refractive index of the gemstone sample. The refractive index parameter 618 may be determined based on the third modified transmitted wave 152 (see FIG. 5) comprising gemstone data 172 which comprise a measure of how the third modified excitation wave 136 is bent or refracted as it enters the gemstone sample 104. Since the refractive index parameter 618 is influenced by the chemical composition and crystal lattice of the gemstone sample 104, the refractive index parameter 618 may aid the identification of the gemstone sample 104. Accordingly, in some embodiments, the refractive index parameter 618 may be compared against one or more reference refractive index parameters, which may be stored in the memory 180, for the identification of the gemstone sample 104.

[0083] Referring to FIG. 6, the processor 170 may be further configured to determine gemstone parameter 174 comprising a species parameter 620 indicative of a class of the gemstone sample 104. The determination of the species parameter 620 may be based on thedetermination of the optical parameters 610 defined above. That is, the species parameter 620 may be determined based on at least one of the UV fluorescence and / or phosphorescence parameter 612, pleochroism parameter 614, absorption parameter 615, birefringence parameter 616, and / or refractive index parameter 618. In various embodiments, the various optical parameter 610 provide information on the lattice structure and arrangement of ions and molecules in the gemstone sample 104, which may assist in the determination of the species of gemstone sample 104. For example, the gemstone sample 104 may be classified as having an isotropic, e.g. cubic; or anisotropic, e.g. tetragonal, hexagonal, trigonal, orthorhombic, monoclinic, triclinic, structure.

[0084] Referring to FIG. 6, the processor 170 may first be configured to, construct, a gemstone sample image 632 from the gemstone data 172 comprised in the image of the gemstone sample 104, in particular, the cross-sectional images of the gemstone sample 104. In various embodiments, the cross-sectional images of the gemstone sample 104 may be comprised in at least one of the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, and / or the first, second, third modified transmitted wave 142, 144, 154. In various embodiments, the gemstone sample image 632 may be constructed from the image of the gemstone sample 104 comprising gemstone data 172 indicative of the color of the gemstone sample 104, i.e. comprised in the first transmitted wave 122, and / or the image of the gemstone sample 104 comprising gemstone data 172 indicative of one or more inclusion properties and / or one or more growth properties of the gemstone sample 104, i.e. comprised in the second transmitted wave 124. In other words, the gemstone sample image 632 may be constructed from the images, for example, cross-sectional images of the gemstone sample 104 acquired, when the imaging device 100 is in a light spectroscopic imaging mode. The first transmitted wave 122 and second transmitted wave 124 may comprise images showing the overall geometric property, e.g. gemstone shape and dimension, and a cut of at least one facet of the gemstone sample 104 and may therefore be particularly suitable for constructing the gemstone sample image 632, and for determining the gemstone shape parameter 636 and the facet parameter 638. In various embodiments, the reconstructed gemstone sample image 632 may comprise a 3D image, and may comprise a plurality of pixels.

[0085] In various embodiments, the processor 170 may be configured to construct the gemstone sample image 632 using one or more tomography techniques, which may include computer-based image reconstruction techniques, such as deep learning models. In some embodiments, the deep learning models may comprise deep learning convolutional neuralnetworks, generative adversarial networks, diffusion models and / or vision transformers. In some embodiments, the processor 170 may be further configured to post-process the constructed gemstone sample image 632 to ensure that the gemstone sample images 632 are sharp, in-focus and have high contrast. As such, the processor 170 may use advance postprocessing algorithms such as focus-stacking and high dynamic-range stacking to improve the image quality of the gemstone sample image 632.

[0086] With reference to FIG. 6, the gemstone parameter 174 may comprise a geometric parameter 630 indicative of a geometric property of the gemstone sample 104. In various embodiments, the geometric parameter 630 may be determined based on gemstone data 172 comprised in the first modified transmitted wave 142 (see FIG. 4). For example, for determining the geometric parameter 630, the gemstone sample image 632 may be constructed based on the image, for example, cross-sectional image, of the gemstone sample 104, which may be comprised in the first modified transmitted wave 142.

[0087] In various embodiments, the geometric parameter 630 may comprise a gemstone shape parameter 636 indicative of a shape and dimension of the gemstone sample 104. Nonlimiting examples of the shape of the gemstone sample 104 may include a round shape, an oval shape, a square shape, a rectangular shape, a heart shape.

[0088] To determine the gemstone shape parameter 636, the processor 170 may be configured to: compare, the gemstone sample image 632 with each of a plurality of reference gemstone sample images 634, each reference gemstone sample image 634 comprising a reference shape and dimension 634a of the reference gemstone sample image 634. In various embodiments, the shape and dimension of the gemstone sample 104 in a pixel of the gemstone sample image 632 may be compared to the reference shape and dimension 634a in a corresponding reference pixel of the reference gemstone sample image 634. In some embodiments, the comparison of the gemstone sample image 632 with the reference shape and dimension 634a of the reference gemstone sample images 634 may further comprise: determining, a measurement value 632a for at least one part of the gemstone sample image 632; and comparing, the measurement value 632a with a corresponding reference measurement value 634al for at least one part the reference gemstone sample image 634. For example, the processor 170 may be configured to determine, the measurement value 632a of one facet of the gemstone sample image 632; and compare, the measurement value 632a with the corresponding reference measurement value 634al of a corresponding facet of the reference gemstone sample image 634. The determination of the measurement value 632a for at least onepart of the gemstone sample image 632 may allow the processor 170 to dimensionally and precisely determine the gemstone shape parameter 636 of the gemstone sample 104.

[0089] The processor 170 may be further configured to, determine, the gemstone shape parameter 636 based on the comparison of the gemstone sample image 632 with each reference gemstone sample image 634. In various embodiments, the processor 170 may be configured to determining the gemstone shape parameter 636 by: determining, whether the shape and dimension of the gemstone sample 104 in the pixel of the gemstone sample image 632 matches, e.g. the same as, equal to, the reference shape and dimension 634a in the corresponding reference pixel of the reference gemstone sample image 634; and determining, the gemstone shape parameter 636 based on the determination whether the shape and dimension of the gemstone sample 104 in the pixel of the gemstone sample image 632 matches the reference shape and dimension 634a in the corresponding reference pixel of the reference gemstone sample image 634. In some embodiments, the processor 170 may be configured to determining the gemstone shape parameter 636 by: determining, whether the measurement value 632a of one facet of the gemstone sample image 632 is equal to the corresponding reference measurement value 634a 1 of the corresponding facet of the reference gemstone sample image 634; and determining the gemstone shape parameter 636 based on said determination.

[0090] Referring to FIG. 6, the geometric parameter 630 may further comprise, a facet parameter 638 indicative of a cut of at least one facet of the gemstone sample 104. Non-limiting examples of the cut of the at least one facet may include a princess cut, an emerald cut, a cushion cut, an oval cut, a marquise.

[0091] To determine the facet parameter 638, the processor 170 may be configured to: compare, the gemstone sample image 632 with each of a plurality of reference gemstone sample images 634, each reference gemstone sample image 634 further comprising a reference cut of at least one facet 634b of the reference gemstone sample image 634. In various embodiments, the cut of at least one facet of the gemstone sample 104 in a pixel of the gemstone sample image 632 may be compared to the reference cut of the at least one facet 634b in a corresponding reference pixel of the reference gemstone sample image 634.

[0092] The processor 170 may be configured to, determine, the facet parameter 638 based on the comparison of the gemstone sample image 632 with each reference gemstone sample image 634. In various embodiments, the processor 170 may be configured to determining the facet parameter 636 by: determining, whether the cut of at least one facet of the gemstone sample 104 in the pixel of the gemstone sample image 632 matches, e.g. the same as, equal to,the reference cut of the at least one facet 634b in the corresponding reference pixel of the reference gemstone sample image 634; and determining, the facet parameter 638 based on the determination whether the cut of the at least one facet of the gemstone sample 104 in the pixel of the gemstone sample image 632 matches that in the reference cut of the at least one facet 634b in the corresponding reference pixel of the reference gemstone sample image 634.

[0093] In various embodiments, the processor 170 may be configured to determine geometric parameter 630 based on at least one of the gemstone shape parameter 636 and / or the facet parameter 638.

[0094] Referring to FIG. 6, the gemstone parameter 174 may further comprise a clarity parameter 640 indicative of a purity of the gemstone sample 104. For example, the clarity parameter 640 may provide an indicator of the presence or absence of one or more imperfections, such as an inclusion, or a growth structure, in the gemstone sample 104. The inclusions and growth structures affect the transparency and visual appearance of the gemstone sample 104. In various embodiments, the clarity parameter 640 may be determined based on gemstone data 172 comprised in the second transmitted wave 124 (see FIG. 1). For example, for determining the clarity parameter 640, the gemstone sample image 632 may be constructed from the images, for example, cross-sectional images of the gemstone sample 104, which may be comprised in the second transmitted wave 124.

[0095] In various embodiments, the clarity parameter 640 may comprise an inclusion parameter 642 indicative of one or more inclusion properties in the gemstone sample, the one or more inclusion properties comprising, a type of the one or more inclusions in the gemstone sample 104. Non-limiting examples of the inclusion type comprises a silk inclusion, a fissure inclusion, a needle inclusion, a crystal inclusion, a snow-ball inclusion. Additionally, or alternatively, the one or more inclusions properties may comprise, a position, e.g. location of the one or more inclusions in the gemstone sample 104.

[0096] To determine the inclusion parameter 642, the processor 170 may be configured to: compare, the gemstone sample image 632 with each of a plurality of reference gemstone sample images 634, each reference gemstone sample image 634 further comprising one or more reference inclusions 634c in the reference gemstone sample image 634. In various embodiments, a pixel of the gemstone sample image 632 may be compared to a corresponding reference pixel comprising the one or more reference inclusions 634c in the reference gemstone sample image 634.

[0097] The processor 170 may be further configured to determine, the inclusion parameter 642 based on the comparison of the gemstone sample image 632 with each of a plurality of reference gemstone sample images 634. In various embodiments, the processor 170 may be configured to determine the inclusion parameter 642 by: determining, whether the pixel of the gemstone sample image 632 matches a corresponding reference pixel comprising the one or more reference inclusions 634c in the reference gemstone sample image 634; and determining the inclusion parameter 642 based on said determination. For example, if it is determined that the pixel of the gemstone sample image 632 matches the corresponding reference pixel comprising the one or more reference inclusions 634c in the reference gemstone sample image 634, it may be determined that the gemstone parameter 642 may be indicative of a presence of the inclusion in the gemstone sample 104. In this example, the processor 170 may be further configured to determine, a type of one or more inclusions and / or a position of the one or more inclusions in the gemstone sample 104. Alternatively, in another example, if it is determined that the pixel of the gemstone sample image 632 does not match the corresponding reference pixel comprising the one or more reference inclusions 634c in the reference gemstone sample image 634, it may be determined that the gemstone parameter 642 may be indicative of an absence of one or more inclusions in the gemstone sample 104.

[0098] In various embodiments, the clarity parameter 640 may further comprise a growth structure parameter 644 indicative of one or more growth structure properties in the gemstone sample 104, the one or more growth structure properties comprising, a mineralization pattern of the one or more growth structures in the gemstone sample 104. Non-limiting examples of the mineralization pattern comprises a planar feature or curved planar feature, a double cross pattern. In addition, the one or more growth structure properties may comprise, a position, e.g. location of the growth structure in the gemstone sample 104.

[0099] To determine the growth structure parameter 644, the processor 170 may be configured to: compare, the gemstone sample image 632 with each of a plurality of reference gemstone sample images 634, each reference gemstone sample image 634 further comprising one or more reference growth structures 634d in the reference gemstone sample image 634. In various embodiments, a pixel of the gemstone sample image 632 may be compared to a corresponding reference pixel comprising the one or more reference growth structures 634d in the reference gemstone sample image 634.

[0100] The processor 170 may be further configured to determine, the growth structure parameter 644 based on the comparison of the gemstone sample image 632 with each of aplurality of reference gemstone sample images 634. In various embodiments, the processor 170 may be configured to determine the growth structure parameter 644 by: determining, whether the pixel of the gemstone sample image 632 matches a corresponding reference pixel comprising the one or more growth structures 634d in the reference gemstone sample image 634; and determining the growth structure parameter 644 based on said determination. For example, if it is determined that the pixel of the gemstone sample image 632 matches the corresponding reference pixel comprising the one or more reference growth structures 634d in the reference gemstone sample image 634, it may be determined that the growth structure parameter 644 may be indicative of a presence of the growth structure in the gemstone sample 104. In this example, the processor 170 may be further configured to determine, a mineralization pattern of one or more growth structures and / or a position of the one or more growth structures in the gemstone sample 104. Alternatively, in another example, if it is determined that the pixel of the gemstone sample image 632 does not match the corresponding pixel comprising the one or more reference growth structures 634d in the reference gemstone sample image 634, it may be determined that the growth structure parameter 644 may be indicative of an absence of the one or more growth structures in the gemstone sample 104.

[0101] In various embodiments, the processor 170 may be configured to determine the clarity parameter 640 based on at least one of the inclusion parameter 642 and / or the growth structure parameter 644.

[0102] Referring to FIG. 6, the gemstone parameter 174 may further comprise, an origin parameter 650 indicative of a geological origin of the gemstone sample 104. The natural crystal formation process and geological condition of a gemstone may be distinct to a particular geographical location and / or specific mining area of a gemstone and therefore, the origin parameter 650 may be useful for gemstone sample 104 identification. Conventionally, a trained gemmologist may determine the geological origin based on the visual observation of the gemstone’s inclusion characteristics.

[0103] In various embodiments, the processor 170 may be further configured to determine the origin parameter 650 based on the inclusion parameter 642 of the gemstone sample 104. In various embodiments, the processor 170 may be configured to: compare, the inclusion parameter 642 indicative of the one or more inclusion properties in the gemstone sample 104, the one or more inclusion properties comprising a position of the one or more inclusions, and / or a type of the one or more inclusions in the gemstone sample 104, with each of a plurality of predetermined reference origin parameters 652 of a reference gemstone sample. Thepredetermined reference origin parameters 652 may comprise a reference type and / or a reference position of the one or more reference inclusions in a reference gemstone sample image 634, and its relationship with a particular geographical location and / or specific mining area of the reference gemstone sample image 634.

[0104] The processor 170 may be further configured to determine, the origin parameter 650 based on the comparison of the inclusion parameter 642 with each of a plurality of predetermined reference origin parameters 652. In various embodiments, the processor 170 may be configured to, determine, whether the inclusion parameter 642 matches, e.g. is equal to, the same as, at least one of a plurality of predetermined reference origin parameters 652; and determine, the origin parameter 650 based on said comparison. For example, if it is determined that the inclusion parameter 642 matches at least one of the predetermined reference origin parameters 652, the origin parameter 650 of the gemstone sample 104 may be determined based on the association of the matched predetermined reference origin parameter 652 with the particular geographical location and / or specific mining area of the reference gemstone sample image 634.

[0105] Referring to FIG. 6, the gemstone parameter 174 may further comprise, a treatment parameter 655 indicative of a treatment applied to the gemstone sample 104. Various treatments may be applied to a gemstone sample 104 to enhance its appearance, clarity and color, to affects its commercial value, and therefore, the treatment parameter 655 may be useful for gemstone sample 104 identification and subsequent valuation. Conventionally, a trained gemmologist may determine whether a gemstone sample 104 has been treated, based on visual observations of the gemstone’s inclusion and growth structure characteristics.

[0106] In various embodiments, the processor 170 may be further configured to determine the treatment parameter 655 based on the inclusion parameter 642 and the growth structure parameter 644 of the gemstone sample 104. In various embodiments, the processor 170 may be configured to: compare, the inclusion parameter 642 indicative of the one or more inclusion properties in the gemstone sample 104, the one or more inclusion properties comprising a position of the one or more inclusions, and / or a type of the one or more inclusions in the gemstone sample 104, with each of a plurality of predetermined reference treatment parameters 656 of a reference gemstone sample. The predetermined reference treatment parameters 656 may comprise a reference type and / or a reference position of the one or more reference inclusions in a reference gemstone sample image 634, and its relationship with a particular treatment applied to a reference gemstone sample.

[0107] In various embodiments, the processor 170 may be configured to, determine, whether the inclusion parameter 642 matches, e.g. is equal to, the same as, at least one of a plurality of predetermined reference treatment parameters 656. For example , if it is determined that the inclusion parameter 642 matches at least one of the predetermined reference treatment parameters 656, the treatment parameter 655 may in part, be determined based on the relationship of the matched predetermined reference treatment parameter 656 with the particular treatment applied to the reference gemstone sample.

[0108] In various embodiments, the processor 170 may be further configured to: compare, the growth structure parameter 644 indicative of the one or more growth structure properties in the gemstone sample 104, the one or more growth structure properties comprising a position of the one or more growth structures, and / or a mineralization pattern of the one or more growth structures in the gemstone sample 104, with each of a plurality of predetermined reference treatment parameters 656 of a reference gemstone sample. The predetermined reference treatment parameters 656 may further comprise a reference mineralization pattern and / or a reference position of the one or more reference growth structures in a reference gemstone sample image 634, and its relationship with a particular treatment applied to a reference gemstone sample.

[0109] In various embodiments, the processor 170 may be configured to, determine, whether the growth structure 644 matches, e.g. is equal to, the same as, at least one of a plurality of predetermined reference treatment parameters 656. For example, if it is determined that the growth structure parameter 644 matches at least one of the predetermined reference treatment parameters 656, the treatment parameter 655 may in part, be determined based on the relationship of the matched predetermined reference treatment parameter 656 with the particular treatment applied to the reference gemstone sample.

[0110] Accordingly, the treatment parameter 655 may be based on the comparison of the inclusion parameter 642 and / or the growth structure parameter 644 with each of the plurality of predetermined reference treatment parameter 656. In some embodiments, the treatment parameter 655 may be based on both the inclusion parameter 642 and the growth structure parameter 644.

[0111] FIG. 7 shows (A) a schematic illustration of an exemplary uniform color space 700 for determining a gemstone parameter 174 comprising a color parameter 660 indicative of a color class of the gemstone sample 104; and (B) an exemplary graph 710 of the preassigned color coordinates corresponding to a predetermined color class of a respective referencegemstone sample image 634. Currently, the determination of the color of a gemstone sample 104 is based on the gemmologist’s visual perception of the color of the gemstone sample 104, which may be inconsistent due to variances in human physiology and / or lighting conditions. Gemstone colors are also labelled using wordy descriptors based on the gemmologist’s subjective perception of the gemstone color. For example, blue gemstones of different shades of blue may be labelled as “royal-blue”, “cornflower-blue”, “peacock-blue”, “violetish blue”, “blue” etc., and the color class of a particular gemstone may differ between different gemmologists.

[0112] Presently, there is an absence of an objective, quantitative and standardized measure for determining and labelling the color class of the gemstone sample 104. Further, an acceptable color tolerance for gemstones may vary across the industry depending on the gemmologist and lighting conditions, due to the lack of a reference standardized measure for determining a color of a gemstone sample 104. In addition, determining a color class for the gemstone sample 104 is particularly challenging due to the non-uniform distribution of color throughout the gemstone sample 104, which is dependent on its shape, cut and transparency level, e.g. purity. This non-uniformity is exacerbated by the gemstone sample 104 lustre when viewed from different perspectives as it interacts with the excitation wave 11 . The system 600 of the present disclosure thus provide an objective, quantitative and standardized measure for determining the color parameter 660 to aid in the identification of the gemstone sample 104. Non-limiting examples of the color class of the gemstone sample 104 may comprise, “blue”; “royal-blue”, “cornflower-blue”, “red”, “ruby”, “yellow”, “green”.

[0113] Referring to FIGS. 6 and 7, a perceptually uniform color space 700, such as but not limited to the International Commission on Illumination (CIE) LAB 1976 color space, may be adopted to provide a library including a plurality of reference color parameters 672, each reference color parameter 672 indicative of a preassigned color coordinate corresponding to a predetermined color class of a respective one of the plurality of reference gemstone sample images 634, the preassigned color coordinate assigned with respect to the uniform color space 700. In various embodiments, the uniform color space 700 provides a device-independent 3D color space for measuring the colors of the reference gemstone sample images 634.

[0114] In the example shown in FIG. 7A, the uniform color space 700 may comprise a L* axis 702 defining black (-L*) at one end and white (+L*) at an opposing end; an a* axis 704 representative to green (-a*) - red (+a*) opponent colors and a b* axis 706 representative of the blue -b*) - yellow (+b*) opponent colors; and the color coordinate of a gemstone sample104 may comprise cartesian coordinates on each of the L*, a* and b* axes. In other words, a gemstone sample 104 may be assigned a representative color coordinate having three coordinates, i.e. L* (representative'), a* (representative), b* (representative) value, and the color of the gemstone sample 104 may be represented as a point, e.g. coordinate in the 3D uniform color space 700. Similarly, each predetermined color class of a respective one of the plurality of the reference gemstone sample image 634 may comprise a preassigned color coordinate, i.e. reference L*, a*, b' value.

[0115] To provide a library comprising preassigned color coordinates corresponding to a predetermined color class of a respective one of the plurality of the reference gemstone sample image 634, the processor 170 may include a machine learning algorithm. In various embodiments, the machine learning algorithm may be a deep learning machine learning algorithm, e.g. diffusion model, vision transformer, convolutional neural networks, which may be trained using reference gemstone sample images 634 visually prelabelled with a predetermined color class. In various embodiments, the algorithms may be trained based on a large number of reference gemstone sample images 634, for example at least 10,000 or more, preferably 12,000 reference gemstone sample images 634 visually prelabeled by a trained and experienced gemmologist, with a predetermined color class. Alternatively, it is contemplated that the algorithm may be trained using an unsupervised machine learning model based on the reference gemstone sample images 634.

[0116] The processor 170 may determine, a preassigned color coordinate corresponding to the predetermined color class of the reference gemstone sample images 634, the preassigned color coordinate assigned with respect to the uniform color space 700. To determine the preassigned color coordinate, the processor 170 may be configured to: determine, the centroid coordinate of the predetermined color class; and determine, the preassigned color coordinate as the centroid coordinate, e.g. reference centroid L*, a*, b* value for the predetermined color class. Referring to the example shown in FIG. 7B, one or more reference gemstone sample images 634 may be visually prelabeled as having a predetermined “blue” 712 color class, and the “blue” color class 710 may have a preassigned color coordinate, i.e. “blue” reference £*, a*, b* value on the uniform color space 700. Similarly, one or more reference gemstone sample images 634 may be visually prelabeled as having a predetermined “red” 714 color class, and the “red” color class 714 may have a preassigned color coordinate, i.e. “red” reference £*, a*, b* value e on the uniform color space 700. In other words, each reference gemstone sampleimage 634 among a plurality of reference gemstone sample images 634 may have a preassigned color coordinate, i.e. reference L* , a* , b* value (assigned with respect to the uniform color space 700), corresponding to a predetermined color class, e.g. “blue” 712, “green”, “red” 714, of the reference gemstone sample image 634. In various embodiments, the library may be stored in the memory 180. It is also contemplated that the library may be assembled and stored on another processor, or on a server, e.g. cloud infrastructure.

[0117] FIG. 8 shows an exemplary schematic illustration of various pixel color clusters 800 for determining a representative color parameter 662 indicative of a representative color coordinate of the gemstone sample 104, assigned with respect to a uniform color space in a (A) 3D format; and (B) 2D format. The uniform color space may refer to the uniform color space 700 discussed with reference to FIG. 7A. FIG. 9 shows the comparison of the representative color parameter 662 of the gemstone sample image 632, with a reference color parameter 672, for determining a color score parameter 664.

[0118] Referring to FIGS. 6, 7 A, 7B, 8A, 8B and 9, the processor 170 may first be configured to, determine a representative color parameter 662 indicative of a representative color coordinate assigned with respect to the uniform color space 700. In various embodiments, the gemstone sample image 632 comprises a plurality of pixels, and determining the representative color parameter 662 may comprise: determining, for each pixel of the gemstone sample image 632, a pixel color parameter indicative of a pixel color coordinate assigned with respect to the uniform color space. The pixel color coordinate may refer to the cartesian coordinate, i.e. pixel L*, a*, b* value for the pixel, and each pixel of the gemstone sample image 632 may comprise a respective pixel color coordinate, i.e. pixel U , a*, b* value. .

[0119] In various embodiments, the processor 170 may be further configured to cluster, each pixel ofthe plurality ofpixels into a pixel color cluster of a plurality of pixel color clusters, each pixel color cluster representative of a predetermined color cluster of the gemstone sample image 104. For example, as shown in FIGS. 8A and 8B, the predetermined color cluster may include a primary-color cluster 802, a secondary-color cluster 804 and a tertiary-color cluster 806. In some embodiments, the predetermined color cluster may only include the primary-color cluster 802 and the secondary-color cluster 804. In various embodiments, the clustering of each pixel may be based on the pixel color coordinate, i.e. pixel L*, a*, b* value, of a respective pixel. The processor 170 may be configured to cluster each pixel by implementing an unsupervised clustering algorithm, e.g. Gmeans clustering algorithm, k referring to the numberof predetermined color clusters. In various embodiments, k may be determined using silhouette analysis (in / <-means clustering) for determining the optimal number of predetermined color clusters. In various embodiments, k may be equal to three, i.e. k = 3 comprising a primarycolor cluster 802, a secondary-color cluster 804 and a tertiary-color cluster 806. In some embodiments, k may be equal to two, i.e. k = 2 comprising a primary-color cluster 802, and a secondary-color cluster 804. Alternatively, in some other embodiments, k may be more than three, for example, k may be equal to four, i.e. k = 4 comprising a quaternary-color cluster (not shown), in addition to the primary-color cluster 802, secondary-color cluster 804 and the tertiary-color cluster 806.

[0120] In various embodiments, the processor 170 may be further configured to determine, for each pixel color cluster, e.g. primary-color cluster 802, secondary-color cluster 804, and tertiary-color cluster 806, a first color cluster parameter 661a indicative of a centroid coordinate of a respective pixel color cluster value, which may be assigned with respect to the uniform color space 700. The first color cluster parameter 661a may comprise a centroid coordinate, i.e. coordinate at the center of each respective pixel color cluster. For example, the first color cluster parameter 661a may be represented as having a LI*, al*, bl* value for the primarycolor cluster 802; a L2*, a2*, b2* value for the secondary-color cluster 804; a L3*, a3*, b3* value for the tertiary-color cluster 806; and a L4*, a4*, b4* value for the quaternarycolor cluster (not shown).

[0121] The processor 170 may be further configured to determine, a second color cluster parameter 661b indicative of a weighted average of each of the pixel color coordinates within the respective pixel color cluster. The second color cluster parameter 661b may therefore be a weighted average of the pixel color coordinates of each pixel, that has been clustered into the respective pixel color cluster. In some examples, the second color cluster parameter 661b may be represented as nl for the primary-color cluster 802; n2 for the secondary-color cluster 804; n3 for the tertiary-color cluster 806; and n4 for the quaternary-color cluster (not shown).

[0122] The processor 170 may be further configured to, determine the representative color parameter 662 based on the first color cluster parameter 661a and the second color cluster parameter 662b. In various embodiments, the processor 170 may be further configured to determine, the representative color parameter 662 having the representative color coordinate, i.e. L * (representative'), a * (representative), b * (representative) value, based on Equations (1) to (3) as defined below:where L* (representative) refers to the representative L* coordinate of the representative color parameter 662 on the L* axis 702, Ll*refers to the L* coordinate of the primary-color cluster 802 on the L* axis 702, L2* refers to the L* coordinate of the secondary-color cluster 804 on the L* axis 702; a* (representative) refers to the representative a* coordinate of the representative color parameter 662 on the a*axis 704, al* refers to the a* coordinate of the primary-color cluster 802 on the a* axis 704, a2* refers to the a* coordinate of the secondarycolor cluster 804 on the a* axis 704; b* (representative) refers to the representative b* coordinate of the representative color parameter 662 on the b* axis 706, bl* refers to the b* coordinate of the primary-color cluster 802 on the b* axis 706, b2* refers to the b* coordinate of the secondary-color cluster 804 on the b* axis 706; nl refers to the weighted average of the pixel color coordinates of each pixel within the primary-color cluster 802; and n2 refers to the weighted average of the pixel color coordinates of each pixel within the secondary-color cluster 804.

[0123] In some embodiments, the L* (representative) may further be determined based on L3* referring to the L* coordinate of the tertiary-color cluster 806 on the L* axis 702, and / or L4* referring to the L* coordinate of the quaternary-color cluster (not shown) on the L* axis 702; the a* (representative) may further be determined based on a3* referring to the a* coordinate of the tertiary-color cluster 806 on the a* axis 704, and / or a4* referring to the a* coordinate of the quaternary-color cluster (not shown) on the a* axis 704; the b* (representative) may be further determined based on b3* referring to the b* coordinate of the tertiary-color cluster 806 on the b* axis 706, and / or b4* referring to the b* coordinate of the quaternary-color cluster (not shown) on the b* axis 706; n3 referring to the weighted average of the pixel color coordinates of each pixel within the tertiary-color cluster 806; and n4 referring to the weighted average of the pixel color coordinates of each pixel within the quaternary-color cluster (not shown). For example, when k is equal to three, i.e. k = 3 comprising a primary-color cluster 802, a secondary-color cluster 804 and a tertiary-color cluster 806, the representative color parameter 662 having the representative color coordinate,i.e. L * (representative'), a * (representative), b * (representative) value, may be based on Equations (4) to (6) as defined below:where L* (representative), LI* , L2* have been defined with regard to Equations (1) to (3), and L3* refers to the L* coordinate of the tertiary-color cluster 806 on the L* axis 702; a* (representative), al*, a2* have been defined with regard to Equations (1) to (3), and a3* refers to the a* coordinate of the tertiary-color cluster 806 on the a* axis 704; b* (representative), bl*, b2* have been defined with regard to Equations (1) to (3), and b3* refers to the b* coordinate of the tertiary-color cluster 806 on the b* axis 706; nl, n2 have been defined with regard to Equations (1) to (3), and n3 refers to the weighted average of the pixel color coordinates of each pixel within the tertiary-color cluster 806. The same principle, e.g. Equations (4) to (6), applies when k is equal to four, i.e. k = 4 comprising a primary-color cluster 802, a secondary-color cluster 804, a tertiary-color cluster 806 and a quaternary-color cluster (not shown), and the representative color parameter 662 having the representative color coordinate, i.e. L * (representative), a * (representative), b * (representative) value may further include the parameters: L4* referring to the / / coordinate of the quaternary-color cluster (not shown) on the L* axis 702; a4* referring to the a* coordinate of the quaternarycolor cluster (not shown) on the a* axis 704; b4* refers to the b* coordinate of the quaternarycolor cluster (not shown) on the b* axis 706; and n4 refers to the weighted average of the pixel color coordinates of each pixel within the quaternary-color cluster (not shown).

[0124] In various embodiments, the representative color parameter 662 may be further determined based on the number of pixel color clusters, which may be determined based on the silhouette analysis ( / -means clustering). In some embodiments, k may be an integer, e.g. a positive natural number, i.e. k > 1; and the representative color parameter 662 having the representative color coordinate, i.e. L*k(representative), unrepresentative), bk(representative) value, may be based on Equations (7) to (9) as defined below:Equation (7)where x = 1, 2, 3 ... k — 1; L*k(representative) refers to the representative / / coordinate of the representative color parameter 662 on the L* axis 702 of the / -th pixel color cluster, L(k)* refers to the L* coordinate of the / c-tli pixel color cluster on the L* axis 702; a( (representative) refers to the representative a* coordinate of the representative color parameter 662 on the a* axis 704 of the / -th pixel color cluster, a(k)* refers to the a* coordinate of the / -th pixel color cluster on the a* axis 704; bk(representative) refers to the representative b* coordinate of the representative color parameter on the b* axis 706 of the k- th pixel color cluster; b(k)!refers to the b* coordinate of the / -th pixel color cluster on the b axis 706; and n(k) refers to the weighted average of the pixel color coordinates of each pixel within the / -th pixel color cluster.

[0125] To determine the color parameter 660, the processor 170 may be further configured to: compare, the representative color parameter 662 with each reference color parameters 672 of a plurality of reference color parameters 672 indicative of the preassigned color coordinate corresponding to a predetermined color class of a respective one of the plurality of reference gemstone sample images 634, the preassigned color coordinate assigned with respect to the uniform color space 700. For example, the representative color coordinate, i.e. e L * (representative), a * (representative), b * (representative) value of the representative color parameter 662 may be compared against each preassigned color coordinate, i.e. reference L* , a*, b* value corresponding to the predetermined color class, i.e. reference color parameters 672 for the “red” predetermined color class, reference color parameters 672 for the “green” predetermined color class, reference color parameters 672 for the “blue” 710 predetermined color class.

[0126] In various embodiments, comparing the representative color parameter 662 with each of the reference color parameter 672 may comprise: determining, for each reference color parameter 672, the Euclidian distance AE between the representative color parameter 662 and the respective reference color parameter 672; and comparing, the Euclidian distance AE for each of the representative color parameter 662 and respective reference color parameter 672 pair. The Euclidian distance AE (see FIG. 9) may be representative of a color distance betweenrhe representative color parameter 662 and the respective reference color parameter 672 and may be calculated according to Equation (10) below:Equation (10) where AL refers to the difference in the coordinate value along the L* axis between the representative color parameter 662 and the respective reference color parameter 672; Aa refers to the difference in the coordinate value along the a* axis between the representative color parameter 662 and the respective reference color parameter 672; and Ab refers to the difference in the coordinate value along the b* axis between the representative color parameter 662 and the respective reference color parameter 672. That is, the Euclidian distance AE may refer to the geometric distance between color points on a cartesian coordinate system that may correspond to variations of human color visual perception.

[0127] The processor 170 may be further configured to, determine a color score parameter 664 indicative of a smallest color distance between the representative color parameter 662 and at least one of the reference color parameters 672. In various embodiments, determining the color score parameter 664 may comprise, identifying, the smallest, i.e. least or smallest, Euclidian distance AE value among each of the representative color parameter 662 and respective reference color parameter 672 pair. A lower, i.e. smallest Euclidian distance AE value indicates a smaller perceptual color difference between the representative color parameter 662 and the respective reference color parameter 672 pair, and therefore quantitatively represents the smallest color distance (smaller perceptual color difference) between two colors on the uniform color space 700.

[0128] As shown in FIG. 6, the processor 170 may be further configured to, compare, the color score parameter 664 with a predetermined color tolerance threshold value 674 indicative of a desired deviation between the representative color parameter 662 and the at least one of the reference color parameters 672. The predetermined color tolerance threshold value 674 may be indicative of a desired deviation that is permitted for the gemstone sample image 632 to be labelled with a predetermined color class. In various embodiments, the predetermined color tolerance threshold value 674 may be in the range of 10 to 25, optionally 15 to 20.

[0129] The processor 170 may then determine, the color parameter 660, i.e. predetermined color class of the gemstone sample 104, based on the comparison of the color score parameter 664 with the predetermined color tolerance threshold value 674. In various embodiments, determining the color parameter 660 may comprise, determining, whether the color scoreparameter 664 is less than or equal to the predetermined color tolerance threshold value 674, and determining, the color parameter 660, if it is determined that the color score parameter 664 is less than or equal to the predetermined color tolerance threshold value 674. In other words, the gemstone sample 104 may be labelled according to one of the predetermined color classes corresponding to the reference gemstone sample image 634, if the smallest Euclidian distance AE is less than or equal to the predetermined color tolerance threshold value 674. Accordingly, the gemstone sample 104 may be labelled with the predetermined color class of the reference gemstone sample image 634 having the smallest, i.e. closest Euclidian distance AE to the respective reference color parameter 672.

[0130] While the comparison of the gemstone sample image 632 with respect to each reference gemstone sample images 634 among the plurality of reference gemstone sample images 634 have been discussed above, the disclosure is not limited thereto and it is further contemplated that in some embodiments, the reference gemstone sample image 634 may comprise a plurality of cross-sectional images of a reference gemstone sample, each cross- sectional image comprising the reference shape and dimension 634a, the reference cut of at least one facet 634b, one or more reference inclusion 634c and / or one or more reference growth structures 634d, and / or reference color parameter 672. In this embodiment, each cross-sectional image of the gemstone sample 104, e.g. gemstone data 172 comprised in at least one of the first, second, third, fourth, fifth, sixth, seventh, eighth transmitted wave 122, 124, 126, 128, 129, 141, 143, 152, and / or the first, second, third modified transmitted wave 142, 144, 154, may individually be compared with a corresponding cross-sectional image of the reference gemstone image 634, to determine the various gemstone parameters 174.

[0131] Referring to FIG. 6, the processor 170 may be configured to determine, a unique gemstone signature parameter 690 for the gemstone sample 104, comprising at least two gemstone parameters 174 discussed above. For example, the unique gemstone signature parameter 690 may comprise a combination of at least two of an optical parameter 610, e.g. UV fluorescence and / or phosphoresce parameter 612, pleochroism parameter 614, absorption parameter 615, birefringence parameter 616, and / or refractive index parameter 618; a species parameter 620; a geometric parameter 630, e.g. gemstone shape parameter 636 and / or facet parameter 638; a clarity parameter 640, e.g. inclusion parameter 642 and / or growth structure parameter 644; an origin parameter 650; a treatment parameter 655; and / or a color parameter 660. It is further contemplated that the processor 170 may be configured to determine a gemstone similarity index, where a difference between a unique gemstone signature parameter690 for the gemstone sample 104, and another unique gemstone signature parameter 690 for another gemstone sample 104 may be compared, and a pre-set threshold value may be used to infer and authenticate matching unique gemstone signature parameters 690. The determination of the unique gemstone signature parameter 690 provides traceability and removes the need to tag via laser inscription or with non-removable DNA information, the gemstone sample 104, and therefore preserves that structure of the gemstone sample 104.

[0132] FIG. 10 shows a flowchart of an exemplary method 1000 for manufacturing the imaging device for acquiring at least one image of a gemstone sample, the at least one image comprising gemstone data indicative of an attribute of a gemstone sample, in accordance with another aspect of the disclosure. The imaging device may refer to imaging device 100, 300, 400, 500 discussed with reference to FIGS. 1 to 5, and repeated descriptions are omitted for conciseness.

[0133] Method 1000 may comprise the steps of: providing, a sample holder configured to support the gemstone sample (step 1002); providing, an electromagnetic radiation source configured to generate an excitation wave for transmission to / through the gemstone sample to produce a transmitted wave modified by the gemstone sample (step 1004); providing, at least one optical instrument positioned relative to and optically aligned to the sample holder, and the electromagnetic radiation source, the at least one optical instrument configured to modulate the excitation wave for transmission through the gemstone sample to produce a modified excitation wave, or modulate the transmitted wave to produce a modified transmitted wave (step 1006); and providing, a detector optically aligned to the sample holder, the electromagnetic radiation source, and the at least one optical instrument, the detector configured to detect the transmitted wave and / or the modified transmitted wave, to acquire the at least one image of the gemstone sample (step 1008).

[0134] In various embodiments, the at least one optical instrument may comprise, a first optical instrument positioned between the electromagnetic radiation source and the sample holder, the first optical instrument configured to modulate the excitation wave for transmission through the gemstone sample to produce the modified excitation wave, wherein the first optical instrument comprises: a first polarizing filter, a grating assembly, and / or a prism assembly.

[0135] In various embodiments, the at least one optical instrument may further comprise a second optical instrument positioned between the sample holder and the detector, the second optical instrument configured to modulate the transmitted wave to produce the modified transmitted wave, wherein the second optical instrument comprises a second polarizing filter.

[0136] In various embodiments, the first polarizing filter and / or the second polarizing filter are configured to be rotatable along a horizontal and / or a vertical axis of the first and / or second polarizing filter.

[0137] In various embodiments, the method 1000 may further comprise, providing, a calibrated refractometer scale optically aligned to the sample holder, the electromagnetic radiation source, the at least one optical instrument, and the detector, wherein the at least one optical instrument further comprises an optical plate or hemisphere or hemicylinder positioned adjacent to the sample holder, the optical plate or hemisphere or hemicylinder configured to modulate the excitation wave to produce the modified excitation wave; and to modulate the transmitted wave to produce the modified transmitted wave, and to project the modified transmitted wave onto the calibrated refractometer scale.

[0138] In various embodiments, the sample holder is configured to be rotatable along an abscissa, an ordinate and / or an applicate axis of the sample holder.

[0139] In various embodiments, the method 1000 may further comprise, providing, a sample chamber positioned adjacent to the sample holder, the sample chamber configured to contain an optical fluid, wherein the sample chamber is further configured to receive the sample holder supporting the gemstone sample, such that the gemstone sample is suspended in the optical fluid contained therein.

[0140] In various embodiments, the excitation wave comprises a wavelength ranging between 100 to 3000 tun.

[0141] In various embodiments, the at least one image of the gemstone sample comprises at least one cross-sectional image of the gemstone sample, each cross-sectional image acquired along a longitudinal, sagittal and / or transverse plane of the gemstone sample.

[0142] FIG. 11 shows a flowchart of an exemplary method 1100 for determining a gemstone parameter indicative of the attribute of the gemstone sample, according to another aspect of the disclosure. The method 1100 for determining a gemstone parameter may refer to the system 600 for determining the various gemstone parameters 174 discussed with reference to FIGS. 6 to 9, and repeated descriptions are omitted for conciseness.

[0143] Method 1100 may comprise the steps of: providing, a processor in data communication with the imaging device (step 1102). In various embodiments, the imaging device may refer to imaging device 100, 300, 400, 500 discussed with reference to FIGS. 1 to 5. Method 1100 may further comprise: obtaining, the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample (step 1104); anddetermining, the gemstone parameter based on the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample (step 1106).

[0144] In various embodiments, the processor comprises at least one machine learning algorithm, for determining the gemstone parameter, the machine learning algorithm optionally including a deep learning algorithm. In some embodiments, the deep learning algorithm may comprise a convolutional neural network algorithm, a diffusion model and / or a vision transformer.

[0145] In various embodiments, the gemstone parameter may comprise an optical parameter indicative of an optical property of the gemstone sample, wherein the optical parameter comprises, a refractive index parameter indicative of a refraction index of the gemstone sample; a birefringence parameter indicative of a birefringence property related to a difference between the refractive index of at least two crystallographic axes of the gemstone sample ; a pleochroism parameter indicative of a pleochroism property related to a color spectrum of the at least two crystallographic axes of the gemstone sample; an absorption parameter indicative of a characteristic absorption spectra related to a dispersion of the transmitted wave of the gemstone sample; a UV fluorescence and / or phosphorescence parameter indicative of a characteristic fluorescence and / or phosphorescence related to the transmitted wave of the gemstone sample.

[0146] In various embodiments, the gemstone parameter may further comprise a species parameter indicative of a class of the gemstone sample, wherein determining the species parameter is based on the determination of at least one of the refractive index parameter, the birefringence parameter, the pleochroism parameter, the absorption parameter, the UV fluorescence and / or phosphorescence parameter, of the gemstone sample.

[0147] In various embodiments, the gemstone parameter may further comprise a geometric parameter indicative of a geometric property of the gemstone sample, wherein the geometric parameter comprises, a gemstone shape parameter indicative of a shape and dimension of the gemstone sample, a facet parameter indicative of a cut of at least one facet of the gemstone sample, wherein determining the gemstone shape parameter comprises: constructing, a gemstone sample image from the at least one image of gemstone sample; comparing, the gemstone sample image with each of a plurality of reference gemstone sample images, each reference gemstone sample image comprising a reference shape and dimension of the reference gemstone sample image; determining, the gemstone shape parameter based on the comparison of the gemstone sample image with each reference gemstone sample image comprising the reference shape and dimension of the reference gemstone sample image; wherein determiningthe facet parameter comprises: comparing, the gemstone sample image with each of the plurality of reference gemstone sample images, each reference gemstone sample image further comprising a reference cut of at least one facet of the reference gemstone sample image, determining, the facet parameter based on the comparison of the gemstone sample image with each reference gemstone sample image comprising the reference cut of the at least one facet of the reference gemstone sample image; and wherein the geometric parameter is determined based on, at least one of the gemstone shape parameter and / or the facet parameter.

[0148] In various embodiments, the gemstone parameter may further comprise a clarity parameter indicative of a purity of the gemstone sample, wherein the clarity parameter comprises, an inclusion parameter indicative of one or more inclusion properties in the gemstone sample, the one or more inclusion properties comprising a position of the one or more inclusions, and / or a type of the one or more inclusions, in the gemstone sample; a growth structure parameter indicative of one or more growth structure properties in the gemstone sample, the one or more growth structure properties comprising a position of the one or more growth structures, and / or a mineralization pattern of the one or more growth structures, formed in the gemstone sample; wherein determining the inclusion parameter comprises: comparing, the gemstone sample image with each of the plurality of reference gemstone sample images, each reference gemstone sample image further comprising one or more reference inclusions in the reference gemstone sample image; and determining, the inclusion parameter based on the comparison of the gemstone sample image, with each of the plurality of reference gemstone sample images comprising the one or more reference inclusions in the gemstone sample image; wherein determining the growth structure parameter comprises: comparing, the gemstone sample image with each of the plurality of reference gemstone sample images, each reference gemstone sample image further comprising one or more reference growth structures in the reference gemstone sample image; and determining, the growth structure parameter based on the comparison of the gemstone sample image with each of the plurality of reference gemstone sample images comprising the one or more reference growth structures; and wherein the clarity parameter is determined based on, at least one of the inclusion parameter and / or the growth structure parameter.

[0149] In various embodiments, the gemstone parameter may further comprise an origin parameter indicative of a geological origin of the gemstone sample, wherein determining the origin parameter comprises, comparing, the inclusion parameter with each of a plurality of predetermined reference origin parameters, each predetermined reference origin parameterscomprising a reference type of the one or more reference inclusions and / or a reference position of the one or more reference inclusions of a reference gemstone sample, and its relationship with a particular geographical location; and determining, the origin parameter based on the comparison of the inclusion parameter with each of the plurality of predetermined reference origin parameters.

[0150] In various embodiments, the gemstone parameter may comprise a treatment parameter indicative of a treatment applied to the gemstone sample, wherein the processor is further configured to: compare, the inclusion parameter with each of a plurality of predetermined reference treatment parameters, each predetermined reference treatment parameter comprising a reference type of the one or more reference inclusions and / or a reference position of the one or more reference inclusions, and its relationship with a particular treatment applied to the reference gemstone sample; compare, the growth structure parameter with each of the plurality of predetermined treatment parameters, each predetermined reference treatment parameter further comprising a reference position of the one or more reference growth structures and / or a reference mineralization pattern of the one or more reference growth structures, and its relationship with the particular treatment applied to the reference gemstone sample; and determine, the treatment parameter based on the comparison of the inclusion parameter and / or the growth structure parameter with each of the plurality of predetermined reference treatment parameters.

[0151] In various embodiments, the gemstone parameter may comprise a color parameter indicative of a color class of the gemstone sample, wherein determining the color parameter comprises: determining, a representative color parameter indicative of a representative color coordinate assigned with respect to a uniform color space, comparing, the representative color parameter with each reference color parameter among a plurality of reference color parameters, each reference color parameter indicative of a preassigned color coordinate corresponding to a predetermined color class of a respective one of the plurality of reference gemstone sample images, the preassigned color coordinate assigned with respect to the uniform color space, determining, a color score parameter indicative of a smallest color distance between the representative color parameter and at least one of the reference color parameters, comparing, the color score parameter with a predetermined color tolerance threshold value indicative of a desired deviation between the representative color parameter and the at least one of the reference color parameters, determining, the color parameter based on the comparison of the color score parameter with the predetermined color tolerance threshold value.

[0152] In some embodiments, the gemstone sample image comprises a plurality of pixels, and determining the representative color parameter may comprise: determining, a pixel color parameter for each pixel of the plurality of pixels, the pixel color parameter indicative of a pixel color coordinate assigned with respect to the uniform color space; clustering, each pixel of the plurality of pixels into a pixel color cluster of a plurality of pixel color clusters, each pixel color cluster representative of a predetermined color cluster of the gemstone sample image, the clustering of each pixel based on the pixel color coordinate of a respective pixel, determining, for each pixel color cluster, a first color cluster parameter indicative of a centroid coordinate of a respective pixel color cluster, and a second color cluster parameter indicative of a weighted average of each of the pixel color coordinate within the respective pixel color cluster, and determining, the representative color parameter based on the first color cluster parameter and the second color cluster parameter.

[0153] In various embodiments, determining the color parameter further comprises, determining, whether the color score parameter is less than or equal to the predetermined color tolerance threshold value, and determining, the color parameter if it is determined that the color score parameter is less than or equal to the predetermined color tolerance threshold value.

[0154] In various embodiments, method 1100 may further comprise: determining, a unique gemstone signature for the gemstone sample, the unique gemstone signature comprising at least two gemstone parameters of the gemstone sample (step 1108).

[0155] According to yet another aspect of the disclosure, there is provided a computer readable medium comprising instructions, which when executed by the processor, causes the processor to perform the method 1100 for determining the gemstone parameter 174.

[0156] The present disclosure thus provides an improved imaging device for acquiring gemstone data indicative of an attribute of the gemstone sample, and a system comprising the improved imaging device for determining a gemstone parameter based on the gemstone data. In this regard, the improved imaging device integrates various gemstone analytical tools in a single device and further includes a detector for acquiring the images of the gemstone sample comprising gemstone data required for gemstone identification. In addition, the system of the present disclosure includes a processor having at least one machine learning algorithm for analyzing the gemstone data, and determining the gemstone parameter based on the gemstone data, for gemstone sample identification. The disclosure also provides an objective and quantitative measure for determining a gemstone color, which is device-independent, not subject to ambient conditions, and provides a platform for calculating a color differencebetween two gemstones, and for describing and comparing gemstone colors in a consistent manner. In addition, the disclosure provides means for determining a unique gemstone signature for tracking a gemstone, that preserves the original structure and value of the gemstone.

[0157] While the disclosure has been particularly shown and described with reference to specific embodiments, it should be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the disclosure as defined by the appended claims. The scope of the disclosure is thus indicated by the appended claims and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced.

Claims

CLAIMS1. An imaging device for acquiring at least one image of a gemstone sample, the at least one image comprising gemstone data indicative of an attribute of the gemstone sample, the imaging device comprising a sample holder configured to support the gemstone sample; an electromagnetic radiation source configured to generate an excitation wave for transmission to / through the gemstone sample to produce a transmitted wave modified by the gemstone sample; at least one optical instrument positioned relative to and optically aligned to the sample holder, and the electromagnetic radiation source, the at least one optical instrument configured to, modulate the excitation wave for transmission to / through the gemstone sample to produce a modified excitation wave, or modulate the transmitted wave to produce a modified transmitted wave; and a detector optically aligned to the sample holder, the electromagnetic radiation source, and the at least one optical instrument, wherein the detector is configured to detect the transmitted wave and / or the modified transmitted wave which is incident on the detector, to acquire the at least one image of the gemstone sample.

2. The imaging device of claim 1, wherein the at least one optical instrument comprises a first optical instrument positioned between the electromagnetic radiation source and the sample holder, the first optical instrument configured to modulate the excitation wave for transmission through the gemstone sample to produce the modified excitation wave, wherein the first optical instrument comprises: a first polarizing filter, a grating assembly, and / or a prism assembly.

3. The imaging device of claim 1 or 2, wherein the at least one optical instrument further comprises a second optical instrument positioned between the sample holder and the detector, the second optical instrument configured to modulate the transmitted wave to produce the modified transmitted wave, wherein the second optical instrument comprises a second polarizing filter.

4. The imaging device of claim 3, wherein the first polarizing filter and / or the second polarizing filter are configured to be rotatable along a horizontal and / or a vertical axis of the first and / or second polarizing filter.

5. The imaging device of any one of claims 1 to 4, further comprising a calibrated refractometer scale optically aligned to the sample holder, the electromagnetic radiation source, the at least one optical instrument, and the detector, wherein the at least one optical instrument further comprises an optical plate or hemisphere or hemicylinder positioned adjacent to the sample holder, the optical plate or hemisphere or hemicylinder configured to modulate the excitation wave to produce the modified excitation wave; and to modulate the transmitted wave to produce the modified transmitted wave, and to project the modified transmitted wave onto the calibrated refractometer scale.

6. The imaging device of any one of claims 1 to 5, wherein the sample holder is configured to be rotatable along an abscissa, an ordinate and / or an applicate axis of the sample holder.

7. The imaging device of any one of claims 1 to 6, further comprising a sample chamber positioned adjacent to the sample holder, the sample chamber configured to contain an optical fluid, wherein the sample chamber is further configured to receive the sample holder supporting the gemstone sample, such that the gemstone sample is suspended in the optical fluid contained therein.

8. The imaging device of any one of claims 1 to 7, wherein the excitation wave comprises a wavelength ranging between 100 to 3000 nm, optionally between 250 to 700 nm.

9. The imaging device of any one of claims 1 to 8, wherein the at least one image of the gemstone sample, comprises at least one cross-sectional image of the gemstone sample, each cross-sectional image acquired along a longitudinal, sagittal and / or transverse plane of the gemstone sample.

10. A system for determining a gemstone parameter indicative of the attribute of the gemstone sample, the system comprising the imaging device according to any one of claims 1 to 9, a processor in data communication with the imaging device, the processor configured to obtain, the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample; and determine, the gemstone parameter based on the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample.

11. The system of claim 10, wherein the processor comprises at least one machine learning algorithm, for determining the gemstone parameter, the machine learning algorithm optionally comprising a deep learning algorithm.

12. The system of claims 10 or 11, wherein the gemstone parameter comprises an optical parameter indicative of an optical property of the gemstone sample, wherein the optical parameter comprises, a refractive index parameter indicative of a refraction index of the gemstone sample; a birefringence parameter indicative of a birefringence property related to a difference between the refractive index of at least two crystallographic axes of the gemstone sample; a pleochroism parameter indicative of a pleochroism property related to a color spectrum of the at least two crystallographic axes of the gemstone sample; an absorption parameter indicative of a characteristic absorption spectra related to a dispersion of the transmitted wave of the gemstone sample; a UV fluorescence and / or phosphorescence parameter indicative of a characteristic fluorescence and / or phosphorescence related to the transmitted wave of the gemstone sample.

13. The system of claim 12, wherein the gemstone parameter further comprises a species parameter indicative of a class of the gemstone sample,wherein determining the species parameter is based on the determination of at least one of the refractive index parameter, the birefringence parameter, the pleochroism parameter, the absorption parameter, the UV fluorescence and / or phosphorescence parameter, of the gemstone sample.

14. The system of any one of claims 10 to 13, wherein the gemstone parameter further comprises a geometric parameter indicative of a geometric property of the gemstone sample, wherein the geometric parameter comprises, a gemstone shape parameter indicative of a shape and dimension of the gemstone sample, a facet parameter indicative of a cut of at least one facet of the gemstone sample, wherein the processor is further configured to: construct, a gemstone sample image from the at least one image of the gemstone sample; compare, the gemstone sample image with each of a plurality of reference gemstone sample images, each reference gemstone sample image comprising a reference shape and dimension of the reference gemstone sample image, and further comprising a reference cut of at least one facet of the reference gemstone sample image; determine, the gemstone shape parameter based on the comparison of the gemstone sample image with each reference gemstone sample image comprising the reference shape and dimension of the reference gemstone sample image; determine, the facet parameter based on the comparison of the gemstone sample image with each reference gemstone sample image comprising the reference cut of the at least one facet of the reference gemstone sample image; and determine, the geometric parameter based on, at least one of the gemstone shape parameter and / or the facet parameter.

15. The system of claim 14, wherein the gemstone parameter further comprises a clarity parameter indicative of a purity of the gemstone sample, wherein the clarity parameter comprises, an inclusion parameter indicative of one or more inclusion properties in the gemstone sample, the one or more inclusion properties comprising a position of the one or more inclusions, and / or a type of the one or more inclusions, in the gemstone sample;a growth structure parameter indicative of one or more growth structure properties in the gemstone sample, the one or more growth structure properties comprising a position of the one or more growth structures, and / or a mineralization pattern of the one or more growth structures, formed in the gemstone sample; wherein the processor is further configured to: compare, the gemstone sample image with each of the plurality of reference gemstone sample images, each reference gemstone sample image further comprising one or more reference inclusions in the reference gemstone sample image, and further comprising one or more reference growth structures in the reference gemstone sample image; determine, the inclusion parameter based on the comparison of the gemstone sample image, with each of the plurality of reference gemstone sample images comprising the one or more reference inclusions in the gemstone sample image, determine, the growth structure parameter based on the comparison of the gemstone sample image with each of the plurality of reference gemstone sample images comprising the one or more reference growth structures; and determine, the clarity parameter based on, at least one of the inclusion parameter and / or the growth structure parameter.

16. The system of claim 15, wherein the gemstone parameter further comprises an origin parameter indicative of a geological origin of the gemstone sample, wherein the processor is further configured to: compare, the inclusion parameter with each of a plurality of predetermined reference origin parameters, each predetermined reference origin parameter comprising a reference type of the one or more reference inclusions and / or a reference position of the one or more reference inclusions of a reference gemstone sample, and its relationship with a particular geographical location; and determine, the origin parameter based on the comparison of the inclusion parameter with each of the plurality of predetermined reference origin parameters.

17. The system of claim 16, wherein the gemstone parameter further comprises a treatment parameter indicative of a treatment applied to the gemstone sample, wherein the processor is further configured to:compare, the inclusion parameter with each of a plurality of predetermined reference treatment parameters, each predetermined reference treatment parameter comprising a reference type of the one or more reference inclusions and / or a reference position of the one or more reference inclusions, and its relationship with a particular treatment applied to the reference gemstone sample; compare, the growth structure parameter with each of the plurality of predetermined treatment parameters, each predetermined reference treatment parameter further comprising a reference position of the one or more reference growth structures and / or a reference mineralization pattern of the one or more reference growth structures, and its relationship with the particular treatment applied to the reference gemstone sample; and determine, the treatment parameter based on the comparison of the inclusion parameter and / or the growth structure parameter with each of the plurality of predetermined reference treatment parameters.

18. The system of any one of claims 14 to 17, wherein the gemstone parameter comprises a color parameter indicative of a color class of the gemstone sample, wherein the processor is further configured to: determine, a representative color parameter indicative of a representative color coordinate assigned with respect to a uniform color space, compare, the representative color parameter with each of a plurality of reference color parameters, each reference color parameter indicative of a preassigned color coordinate corresponding to a predetermined color class of a respective one of the plurality of reference gemstone sample images, the preassigned color coordinate assigned with respect to the uniform color space, determine, a color score parameter indicative of a smallest color distance between the representative color parameter and at least one of the reference color parameters, compare, the color score parameter with a predetermined color tolerance threshold value indicative of a desired deviation between the representative color parameter and the at least one of the reference color parameters, determine, the color parameter based on the comparison of the color score parameter with the predetermined color tolerance threshold value.

19. The system of claim 18, wherein the gemstone sample image comprises a plurality of pixels, wherein the processor is configured to determine the representative color parameter by, determining, a pixel color parameter for each pixel of the plurality of pixels, the pixel color parameter indicative of a pixel color coordinate assigned with respect to the uniform color space; clustering, each pixel of the plurality of pixels into a pixel color cluster of a plurality of pixel color clusters, each pixel color cluster representative of a predetermined color cluster of the gemstone sample image, the clustering of each pixel based on the pixel color coordinate of a respective pixel, determining, for each pixel color cluster, a first color cluster parameter indicative of a centroid coordinate of a respective pixel color cluster, and a second color cluster parameter indicative of a weighted average of each of the pixel color coordinate within the respective pixel color cluster, and determining, the representative color parameter based on the first color cluster parameter and the second color cluster parameter.

20. The system of claim 18 or 19, wherein to determine the color parameter, the processor is further configured to, determine, whether the color score parameter is less than or equal to the predetermined color tolerance threshold value, and determine, the color parameter if it is determined that the color score parameter is less than or equal to the predetermined color tolerance threshold value.

21. The system of any one of claims 10 to 20, wherein the processor is further configured to determine, a unique gemstone signature for the gemstone sample, the unique gemstone signature comprising at least two gemstone parameters of the gemstone sample.

22. A method of manufacturing an imaging device for acquiring at least one image of a gemstone sample, the at least one image comprising gemstone data indicative of an attribute of the gemstone sample, the method comprising providing, a sample holder configured to support the gemstone sample;providing, an electromagnetic radiation source configured to generate an excitation wave for transmission to / through the gemstone sample to produce a transmitted wave modified by the gemstone sample; providing, at least one optical instrument positioned relative to and optically aligned to the sample holder, and the electromagnetic radiation source, the at least one optical instrument configured to modulate the excitation wave for transmission through the gemstone sample to produce a modified excitation wave, or modulate the transmitted wave to produce a modified transmitted wave; and providing, a detector optically aligned to the sample holder, the electromagnetic radiation source, and the at least one optical instrument, the detector configured to detect the transmitted wave and / or the modified transmitted wave which is incident on the detector, to acquire the at least one image of the gemstone sample.

23. A method for determining a gemstone parameter indicative of the attribute of the gemstone sample, the method comprising providing, a processor in data communication with the imaging device of any one of claims 1 to 9, wherein the method further comprises, obtaining, the at least one image of the gemstone sample comprising gemstone data indicative of the attribute of the gemstone sample; determining, the gemstone parameter based on the at least one image of the transmitted wave and / or the modified transmitted wave comprising gemstone data indicative of the attribute of the gemstone sample, and optionally determining, a unique gemstone signature for the gemstone sample, the unique gemstone signature comprising at least two gemstone parameters of the gemstone sample.

24. The method of claim 23, wherein the processor comprises at least one machine learning algorithm, for determining the gemstone parameter, the machine learning algorithm optionally comprising a deep learning algorithm.

25. A computer readable medium comprising instructions, which when executed by the processor, causes the processor to perform the method of claim 23 or 24.

Images