High clarity gemstone facet and internal imaging analysis

Abstract

Systems and methods herein may be used for setting up gemstone image capture, such as high-clarity-level diamonds. The present embodiments may provide methods of capturing diamond surface and internal clarity features from diamond mesas and through facets, as well as other facets. Systems and methods may be used to convert gemstone size information into azimuth angle, slope, and distance information, and to adjust the motorized pan-tilt accordingly for surface imaging. In addition, the calibration method may account for an offset between the designed and actual system alignments. A calibration process may be used to compensate for the offset. In addition, additional transitions may be made to compensate for excursions caused by gemstone geometry. These methods can automatically capture surface reflection images on a gemstone facet and internal features taken through the gemstone facet.

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 409,696, filed on September 23, 2022, the entire content of which is incorporated herein by reference. Technical Field

[0003] This field includes lighting, image capture, and analysis systems and methods for evaluating the clarity of diamonds or other gemstones. Background Art

[0004] Many imaging systems may not be able to perform automatic clarity grading of diamonds with high clarity grades. Instead, such analysis may need to be done manually based on visual assessment. For example, current clarity grading instruments do not have sufficient spatial resolution, proper lighting conditions to highlight fine features, the ability to examine a diamond from all facets, the ability to scan an entire diamond sample, and / or the ability to separate surface and internal features. Current clarity grading may only be able to detect diamonds with clarity grades lower than "VS", which may include approximately 72% of common diamonds. Current instrument - based clarity grading systems may not be able to detect high - clarity diamonds. The clarity grading of high - clarity grade diamonds is done by visual assessment. The remaining VVS2 (13%), VVS1 (11%), IF (3%), and Flawless (<1%) diamonds generally cannot be graded consistently. The systems and methods herein can address these deficiencies to image and grade high - clarity diamonds and other gemstones. Summary of the Invention

[0005] The systems and methods herein can be used to provide a way to analyze high - clarity gemstones in an easily repeatable manner and produce reliable results.

[0006] The systems and methods of the present disclosure may include: illuminating the table of a sample diamond with diffused light via a computer in communication with at least one light source and a digital camera; causing the digital camera to capture a surface image of the diamond table under diffused light via the computer; illuminating the facets of the sample diamond other than the table with collimated light via the computer; causing the digital camera to capture a surface image of the diamond facets other than the table under collimated light via the computer; illuminating the table of the sample diamond with dark field illumination via the computer; causing the digital camera to capture internal images of the diamond table at multiple depths of focus under dark field illumination via the computer; causing the digital camera to capture internal images of the diamond facets other than the table through the pavilion or crown at multiple depths of focus under dark field illumination via the computer. The systems and methods may additionally or alternatively include analyzing the captured digital surface images of the diamond table and the digital surface images of the diamond facets other than the table via the computer to detect anomalies. The systems and methods may additionally or alternatively include analyzing the captured digital internal images of the diamond table and the digital internal images through the surface of the diamond facets other than the table via the computer to detect anomalies. The systems and methods may additionally or alternatively include assigning a clarity grade to the sample diamond via the computer based on the analyzed digital surface images of the diamond table, the digital surface images of the diamond facets other than the table, the digital internal images of the diamond table, and the digital internal images of the diamond facets other than the table. The systems and methods may additionally or alternatively include taking multiple internal images with a focused scan step of 0.3 mm to match the depth of field of the camera. The systems and methods may additionally or alternatively include: the digital camera images of the diamond facets other than the table captured under collimated light include images captured at 16 different azimuth angles. The systems and methods may additionally or alternatively include: the digital camera images of the diamond facets other than the table captured under collimated light include all other surface images. The systems and methods may additionally or alternatively include that the digital camera images of the captured internal images include 96 internal images, with a focused scan step of, for example but not limited to, 0.25 mm or 0.3 mm.The method and system may additionally or alternatively include the computer analyzing the surface image by locating the surface and surface arrival features from the surface image of each facet by using boundary analysis or contrast comparison of pixels within each image; the computer identifying the types of surfaces and surface arrival features in the image, where the types include feathers, pits, scratches, polish lines, surface texture, or burns; the computer classifying the degree of the surfaces and surface arrival features based on the size and contrast of the surface features by comparing the detected inclusion size and contrast with previously determined thresholds; the computer analyzing the internal image by locating the internal and surface arrival internal features from the captured internal digital images at different azimuth angles and depths; the computer identifying the types of the internal and surface arrival internal features, where the types include feathers, needles, clouds, or internal texture; the computer differentiating the internal inclusions by using surface analysis; the computer classifying the degree of the internal and surface arrival internal features based on the size and contrast of the internal features by using pixel counting and contrast; the computer generating a clarity grade by using surface and internal analysis.

[0007] Additionally or alternatively, the systems and methods herein may include: capturing an image of a gemstone to determine a clarity grade; obtaining a wireframe model of the gemstone by a computer in communication with a digital camera, where the gemstone is located on a turntable; the computer calculating the azimuth angle (φ), the tilt angle (θ), and the distance (d) from the camera to each facet of the gemstone by using the wireframe model; the computer sending instructions to a turntable motor configured to rotate the turntable, a tilt motor configured to adjust the tilt of the camera to the turntable, and a focus adjustment motor configured to adjust the focus of the camera to the turntable, and sending instructions to the camera and a light source to illuminate the turntable and the gemstone and capture images of each facet of the gemstone in sequence; the computer adjusting the tilt motor to move the camera to an angle of approximately 45 degrees with respect to the first facet, causing the dark field light source to illuminate the gemstone, and capturing the dark field images of each gemstone facet.

[0008] Additionally or alternatively, the systems and methods herein may include a computer with a processor and memory, the computer being in communication with at least one light source and a digital camera, the computer configured to illuminate a sample diamond table with diffused light, wherein the sample diamond is configured on a turntable; cause the digital camera to capture a surface image of the diamond table under diffused light; illuminate the facets of the sample diamond other than the table with collimated light; cause the digital camera to capture a surface image of the facets of the diamond other than the table under collimated light; illuminate the sample diamond table with darkfield illumination; cause the digital camera to capture internal images of the diamond table at multiple depths of focus under darkfield illumination; and cause the digital camera to capture internal images of the facets of the diamond other than the table at multiple depths of focus under darkfield illumination. Additionally or alternatively, the system further includes a turntable motor configured to rotate the turntable, an incline motor configured to adjust the incline of the digital camera with respect to the turntable, and a focus adjustment motor configured to adjust the focus of the digital camera with respect to the turntable. Additionally or alternatively, the system further includes a backlit silhouette light source and a silhouette camera configured to capture multiple digital silhouette images of a sample gemstone on a rotating turntable. Additionally or alternatively, the computer is further configured to analyze the surface images by using boundary analysis or contrast comparison of pixels within each image to locate surface and surface-reaching features from the surface images of each facet; identify the types of surface and surface-reaching features in the images, wherein the types include feathers, pits, scratches, polish lines, surface texture, or burns; classify the extent of the surface and surface-reaching features based on the size and contrast of the surface features by comparing the detected inclusion size and contrast with previously determined thresholds; analyze the internal images by locating internal and surface-reaching internal features from the captured internal digital images at different azimuth angles and depths; identify the types of internal and surface-reaching internal features, wherein the types include feathers, needles, clouds, or internal texture; use surface analysis to distinguish inclusions; use pixel counting and contrast to classify the extent of the internal and surface-reaching internal features based on the size and contrast of the internal features; and generate a clarity grade using surface and internal analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] To better understand the embodiments described in this application, reference should be made to the following detailed description taken in conjunction with the accompanying drawings, in which like reference numerals refer to corresponding parts throughout the figures.

[0010] Figure 1A-1B Shows an example hardware setup of equipment that can be used to employ the methods described herein.

[0011] Figure 2A Is a side view of an example azimuth imaging camera and a gemstone on a turntable according to certain aspects described herein.

[0012] Figure 2B Is an example diagram showing a size measurement output according to certain aspects described herein.

[0013] Figure 2C It is a view of a gemstone on an azimuth imaging camera and a gimbal according to certain aspects described herein.

[0014] Figure 3A-3B It is an illustration of the surface clarity characteristics of a diamond according to certain aspects described herein.

[0015] Figure 4A-4C Various example surface clarity characteristics are shown according to certain aspects described herein.

[0016] Figure 5A-5B Example table-side internal clarity characteristics are shown according to certain aspects described herein.

[0017] Figure 6A-6B A bottom view of example pavilion / waist-side internal clarity characteristics is shown according to certain aspects described herein.

[0018] Figure 7A-7B A pavilion view of example pavilion / waist-side internal clarity characteristics using dark field light is shown according to certain aspects described herein.

[0019] Figure 8A-8B A pavilion view of example pavilion / waist-side internal clarity characteristics using backlight is shown according to certain aspects described herein.

[0020] Figure 9A-9B A diamond depicted with increased lens magnification is shown.

[0021] Figure 10A-10B A diamond switched to dark field light is shown according to certain aspects described herein.

[0022] Figure 11 It is an example method for determining the clarity grade of a high-clarity diamond according to certain aspects described herein.

[0023] Figure 12 It is an example hardware setup of a system for capturing gemstone size information, converting the gemstone size information into azimuth, tilt, and distance information, and correspondingly adjusting an electric gimbal for surface imaging according to certain aspects described herein.

[0024] Figure 13 An example configuration for arm axis calibration in the X direction is shown according to certain aspects described herein.

[0025] Figure 14 An example configuration for arm axis calibration in the X direction is shown according to certain aspects described herein.

[0026] Figure 15 An example configuration for arm axis calibration in the Y direction is shown according to certain aspects described herein.

[0027] Figure 16 An example diagram of a coordinate plane for surface reflection capture according to certain aspects described herein.

[0028] Figure 17 An example diagram of a coordinate plane for a rotating arm according to certain aspects described herein.

[0029] Figure 18 An example diagram of adjusting focus based on a wireframe according to certain aspects described herein.

[0030] Figure 19 An example diagram of the geometric shape relationship of a wireframe according to certain aspects described herein.

[0031] Figure 20 A flowchart of an example workflow for converting gemstone size information into azimuth, inclination, and distance information and correspondingly adjusting a pan-tilt head for surface imaging.

[0032] Figure 21 A diagram of an example networking system according to certain aspects described herein.

[0033] Figure 22 A diagram of an example computer system according to certain aspects described herein. Detailed Description

[0034] Reference will now be made in detail to the embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the subject matter presented herein. However, it will be apparent to one of ordinary skill in the art that the subject matter may be practiced without these specific details. In addition, the specific embodiments described herein are provided by way of example and should not be used to limit the scope of the specific embodiments. In other instances, well-known data structures, time schemes, software operations, programs, and components have not been described in detail so as not to unnecessarily obscure various aspects of the embodiments herein.

[0035] Overview

[0036] In some examples, diamonds of high clarity grade refer to diamond rough stones that contain only clarity features that are invisible to the human naked eye, such as inclusions or surface scratches. Due to the rarity of high-clarity diamonds, their commercial value is much higher than that of other diamonds with lower clarity grades. Currently, the schemes used to evaluate high-clarity diamonds rely on gemologists to visually observe with the aid of a small magnifying glass (10x magnifier) and a gemological microscope. The gemologist can first use the small magnifying glass to detect the clarity features and then use the microscope to visually identify the types of clarity features with the naked eye. Each sample may need to be inspected from all facets, and the clarity features can be manually recorded by the gemologist.

[0037] The evaluation process of high-clarity diamonds can be very time-consuming, and the results may be inconsistent. To be considered a clarity feature, the feature may need to be detectable under a 10x loupe, but this detection can be subjective and depends on the visual ability of the human grader. These clarity features are usually small in size and shallow in depth. Most of these clarity features are difficult to detect from the table side of the gemstone. Additionally, these features can appear anywhere on or within gemstones such as diamonds.

[0038] No automated or computerized clarity grading instrument has sufficient spatial resolution, appropriate lighting conditions to highlight small features, the ability to inspect the diamond from all facets, the ability to scan the entire diamond sample, and / or the ability to separate surface and internal features. For example, current and earlier automated clarity grading can only detect diamonds with clarity grades lower than "VS", which account for approximately 72% of common diamonds. The remaining VVS2 (13%), VVS1 (11%), IF (3%), and flawless (<1%) diamonds may not be graded consistently.

[0039] The systems and methods herein account for these deficiencies and provide such automated and computerized imaging and evaluation. The imaging system described herein can be used to automatically detect small clarity features on or within gemstones such as diamonds. The imaging system described herein can automatically scan the entire gemstone or diamond to detect clarity features and provide a clarity grade for the sample based on the results. The entire process, including evaluation, decision-making, and recording, can be automated, and the imaging system can provide more consistent grading results than manual grading.

[0040] The systems and methods described herein can be used for the automation of the diamond or gemstone grading process and for improving the accuracy and consistency of diamond or gemstone grading. The imaging systems and methods herein can detect internal and surface clarity features of diamonds, such as but not limited to, features as small as 3 micrometers (um) or smaller. The imaging systems and methods herein can also evaluate internal and surface clarity features of diamonds from all facets (e.g., table, crown facets, pavilion facets, and girdle (facets)). The imaging systems and methods herein can also evaluate the clarity features of diamonds from the surface to deep within the diamond. The imaging systems and methods herein can also separate and distinguish the locations of clarity features between internal features, surface-to-internal features, and surface features. The results obtained from the imaging systems and methods herein can be aggregated to provide a final clarity grade. In some cases, the results can identify the type of clarity feature or locate the type of clarity feature from the 3D reconstructed volume of the diamond.

[0041] The described imaging systems and methods can combine multiple imaging systems to capture the fine surface and internal clarity characteristics of diamonds. The imaging systems and methods herein can also be used to determine the imaging systems and illumination environments required for fine clarity characteristics. The imaging systems and methods herein can also determine the required sample adjustments or orientations to capture the fine clarity characteristics of diamonds. The systems and methods herein can automatically detect the fine clarity characteristics of diamonds, collect images of the clarity characteristics required for clarity grading, and identify diamond clarity characteristics based on the data collected to determine the clarity grade of each analyzed diamond or gemstone.

[0042] Examples of surface and internal characteristics

[0043] Two main areas for analyzing high-clarity gemstones are surface characteristics and internal characteristics. For high-clarity gemstones, old methods and hardware setups may miss one or both of the surface and internal characteristics that can affect the overall clarity grade.

[0044] Surface characteristics can be imaged using specular reflection of diffused light on the table of the gemstone. In some examples, to find surface characteristics on other facets, collimated light can be used for specular reflection.

[0045] In some examples, internal characteristics can be found using focus scanning and darkfield light for imaging from the directions of the table and other facets.

[0046] Improved internal characteristic imaging can be used to capture images of needle-sized characteristics, e.g., about 3 microns in size. In some examples, the systems and methods described herein can image characteristics smaller or larger than 3 microns.

[0047] Examples of hardware setups

[0048] Hardware setups for the imaging systems are described herein and shown by way of example in FIG. 1. For the table of the gemstone, specular reflection using diffused light can be used for imaging, while for other facets, specular reflection using collimated light can be used for imaging. FIG. 1 shows an example hardware setup 100 of a device that can be used for the methods described herein. Such a hardware setup may be useful for imaging gemstones as it can include automatic pitch and focus adjustments, a magnification of 1.78× (for imaging inclusions as small as 3 microns), specular reflection (for surface analysis), and automatic focus scanning from the table to the culet. In some examples, the focus scanning step can be 0.3 mm. Internal characteristics can be imaged using focus scanning with darkfield light.

[0049] In this example, multiple component parts can be combined into a single unit. The unit can include a camera arrangement 116, a light source arrangement 102, a gemstone turntable 108, and corresponding lenses, as described herein. In some examples, the light source 118 is a dark-field-like light source. Internal features can be imaged using a focused scan of the dark-field light. In some examples, the camera arrangement 116 is a digital image camera capable of capturing digital images, which generates pixelated image data for analysis by the camera or other computer, as described herein.

[0050] In the example of FIG. 1, the table side of the gemstone 108 is arranged facing the camera 116 so that the camera can focus on the table facets. This arrangement is not intended to be limiting and can include Figure 2A any orientation of the camera relative to the gemstone as described herein or throughout the specification.

[0051] The hardware shown and described in FIG. 1 can have component parts that communicate with a computer, such as those described in FIG. 8 but not shown in FIG. 1. In this way, a single system can adjust and control image capture, illumination, light timing, and image capture timing as described herein to more effectively capture images of the gemstone 106 under various lighting conditions, which can assist in the analysis of high-clarity gemstones 106, as described herein. In this example, a diamond 106 with the table side up is shown, with the table of the gemstone 106 facing the camera 116.

[0052] As shown in FIG. 1, the focus of the emitted light beam 120 is the gemstone 106 arranged in / on the turntable 108. The operator can simply place any number of sample gemstones 106 on the holder or turntable 108 for analysis, or they can be automatically loaded by a robotic arm or other means. Then, the system can move the table turntable 108 and / or other parts of the system 100 to view the gemstone 106 arranged in or on the turntable 108 for analysis. In some examples, the turntable 108 is a translation turntable capable of three-dimensional X, Y, Z movement and / or rotational movement using any of a variety of motors controlled manually or in communication with a computing system, as described herein. The steps in FIG. 1 can quickly and easily analyze multiple samples and greatly simplify the operator's process, otherwise the operator would have to load new gemstones 106 one by one to analyze each different gemstone sample. FIG. 1 shows only one gemstone 106 being analyzed as an example. In other examples, an entire array of gemstones can be configured, and the system can move the turntable 108 by motors as described to align the camera 116 and the light 102 with the gemstone 106 for one analysis, thereby analyzing one gemstone at a time.

[0053] To illuminate the sample gemstone 106 with a uniform excitation wavelength, a beam splitter 130 can be used in some instances. In these instances, the beam splitter 130 can be a 90T / 10R beam splitter. One advantage of using a beam splitter in the systems described herein is that the overall system may be more compact than systems that do not use such an arrangement. The use of the beam splitter allows the incident beam 120 illuminating the gemstone gimbal 108 and the reflected light 128 from the gemstone gimbal 108 and the gemstone under examination 106 to pass through the same component parts 130 and reach the image capture camera assembly 116, which minimizes the space occupied by this arrangement in the laboratory work area. Additionally, this arrangement is user-friendly for operators, who can more easily manipulate, carry, deploy, and / or reposition the compact system than a dispersed system.

[0054] In this instance, the camera 110 and the imaging lens 112 are arranged such that they are aligned with the gimbal 108. In this instance, the camera 110 is also aimed through the beam splitter 130. In various instances, the imaging lens 112 can be a fixed magnification imaging lens, a macro lens (for reducing distortion), a telecentric lens (for long working distances), a manually or electrically adjustable magnification imaging lens (for changing the field of view). The imaging lens can also include manual or electric focusing (such as a digital single-lens reflex camera, DSLR).

[0055] Internal features can be imaged using dark-field light focused scanning. In some instances, an adjustable aperture 114 is arranged in front of the imaging lens 112. In various instances, the magnification of the adjustable camera lens 112 can be, for example but not limited to, a magnification of 1.87 times. This magnification can improve the spatial resolution. In some instances, Z-axis scanning can be used to image multiple focal depths of the gemstone. In some instances, the focused scanning step is 0.3 mm. In some instances, the focused scanning step is 0.2 mm. In some instances, the focused scanning depth is 0.4 mm. Any scanning step can be used, and these are just non-limiting instances.

[0056] In some instances, Z-axis scanning can extend the sensing range of the system. This Z-axis scanning can be accomplished by physically moving the gimbal 108 in the Z direction. In some instances, this Z-axis scanning can be accomplished using different focal depths of the arrangement of the camera 110 and the lens 112.

[0057] This camera arrangement 116 can be housed in a single housing or structure together with other arrangements described herein. In some instances, this camera arrangement 116 is adjustable to adjust the focal length and can also be fixed to or removable from the entire system 100. In some instances, the camera arrangement 116 can be positioned to view the gimbal 108 platform, table, bracket, or other gemstone 106 support to capture an image of the gemstone under examination 106.

[0058] In some instances, the gimbal 108 may include a pre-arranged area within which the field of view of the camera 116 is set. In this pre-arranged area on the gimbal 108, a sample 106 for analysis may be placed so as to be included within the field of view of the camera 116.

[0059] In some instances, the camera arrangement 116 may be positioned such that the field of view includes the gemstone 106 on the gimbal 108 via a beam splitter 130. In some instances, two beam splitters 130 may be arranged in sequence such that the camera arrangement 116 is positioned with the field of view passing through the two beam splitters 130 and then through the gimbal 108. Any number of beam splitters may be arranged similarly, each having its own light source, such as, but not limited to, one, two, three (not shown), four (not shown), five (not shown), six (not shown), or more. Such an arrangement may allow the camera 116 to observe the gimbal 108 through any number of beam splitters, thereby observing any gemstone placed on or within the gimbal 108. The beam splitters may reflect light of different wavelengths from different light sources similar to the depicted light source 102 towards the gimbal 108, as described herein.

[0060] The beam splitter 130 may be used to reflect light of certain wavelength bands and allow light of other wavelength bands to pass through. In such an instance, the beam splitter may be arranged to reflect light from the same number of light sources 102. In such an instance, light 120 may be generated from each light source 102 and the light beam may be directed to be reflected from the beam splitter 130 and towards the gemstone 106 on the gimbal 108. In this way, light from different light sources may be reflected onto the gimbal 108, thereby exciting and / or illuminating any gemstone 106 on the gimbal 108. In such an instance, the excited and / or reflected light 128 may return through the beam splitter 130 and back to the camera 116 for image capture.

[0061] The beam splitter 130 may have different absorption coefficients for polarized light in different directions and may be used to selectively pass light within a small range of wavelengths while reflecting other wavelengths. In some instances, the first beam splitter 130 may direct long-wave UV light to the sample, which reflects light with a wavelength below 395 nm and passes light with a wavelength above 400 nm. In such an instance, the average reflection ratio may be approximately 100:1, which may be sufficient to direct excitation and transmit the luminescence signal. In certain instances, the wavelength of the reflected light may be between 400 - 700 nm. Since the excitation light from the gemstone 106 may have a specific wavelength (between 400 nm - 700 nm), it may pass through the beam splitter 130 rather than being reflected like the initial deep UV light beam 120.

[0062] In some instances, the beam splitter 130 may reflect light with a wavelength less than 300 nm and allow light with a wavelength greater than 300 nm to pass through. In some instances, the excitation wavelength is between 10 nm and 400 nm.

[0063] In some instances, the first light source 102 may be an ultraviolet (UV) light-emitting diode (LED) light source. A UV LED light source, an LED light source, a xenon flash lamp, and / or a laser with a wavelength between 350 nm and 410 nm may be used. Examples of UV LEDs and xenon flash lamps are only non-limiting examples. Other types of light sources may also be arranged with the corresponding beam splitters in any number and order. In some instances, the light source 102 is a laser-driven light source (LDLS). In some instances, the light source 102 may be a deuterium lamp. In some instances, the light source 102 may be a 224.3 nm HeAg laser.

[0064] In some instances, a computer system communicates with the described optical system. In such instances, the computer may control the power-on time of the light source 102, or turn the light source 102 on or off, so as to direct different light combinations to the turntable 108 at different times, thereby irradiating and / or exciting the gemstone 106 placed there. Then, the camera 116 may capture the excitation light or reflected light 128 from the gemstone 106, which returns through the two beam splitters 130 back to the camera lens 112 and the image capture camera 110.

[0065] Regardless of how many independent light beams are directed at the gemstone 106 turntable 108, they can be excited and / or reflected 128 and return through the beam splitters 130 (regardless of how many are arranged) and the adjustable aperture 114 (if any), the camera lens 112, and the image capture camera 110.

[0066] In addition, in some instances, the LED light panel 118 may be arranged to surround or otherwise align with the turntable 108 to irradiate the gemstone 106 from different angles. In some instances, the surrounding light source 118 may be a white light LED, which may cover a wavelength range of 400 nm to 700 nm. In some instances, the light source 118 is a dark field light source. In some instances, such a light source 118 has a white light LED color temperature between 2,800 K and 6,500 K, and in some instances is 5,000 K. The color rendering index (CRI) value may range from 80 to 98. In some instances, white light LEDs with a CRI greater than 90 may be used.

[0067] Then, the camera 110 can digitally receive and / or capture excitation and / or reflection images of the gemstone 106 for analysis, as described herein. In combination with multiple light sources that sequentially illuminate the gemstone 106 and the gimbal 108, the camera imaging system 110 can collect / capture corresponding images by automatically controlling the light sources 102 and timed image capture, such as but not limited to, white light images, long-wave fluorescence images, short-wave fluorescence images, and / or phosphorescence images. In some instances, multiple image captures can be performed corresponding to any one of the various light source illuminations, and the image capture timing can be set to the corresponding illumination. As described herein, representative colors and luminances can be calculated from the images captured of any fluorescence and phosphorescence.

[0068] In some instances, the camera arrangement 116 can include a Z-adjustment mechanism 150. Such a mechanism can be or include a motor, bearings, rails, rollers, screws, pulleys, gears, levers, or any other type of machine, whether manually or motor-driven, capable of moving the camera assembly 116 up and down relative to the gemstone gimbal 108. In some instances, the gimbal 108 can be moved relative to the camera assembly 116. In some instances, the camera 116 and the gimbal 108 can move relative to each other.

[0069] Such images can include color pixelated data representing the fluorescence image of the gemstone, as described herein. The camera 110 can include computer components, such as described in FIGS. 7 and 8, and can also communicate with other computer components as described herein for timing camera image capture, processing the pixelated digital images, for saving, storing, sending, and / or otherwise analyzing or manipulating the pixelated digital images of the gemstone table.

[0070] Figure 1B More detailed illustration of Figure 1A Another example of Figure 1B Includes the camera 110, an electric aperture 114, side light sources 102, a gimbal or sample holder 108, a dark field light source 118, an imaging lens 112, a beam splitter 130 (e.g., a 90T / 10R beam splitter or other beam splitter). And Figure 1B Also shown is a Z-axis electric gimbal 140, an electric gimbal 142 for magnification control, an electric variable aperture 144, and an electric universal joint gimbal 146. Figure 1A And Figure 1B Intended to depict hardware components that can be used in any combination or arrangement as described herein.

[0071] Azimuth example

[0072] Side views can be used to obtain a wireframe model of a sample gemstone, capture surface images of each facet, and are achieved using multiple different azimuth angles, e.g., 16 different azimuth angles. This method can be used to capture multiple surface images, e.g., but not limited to 56 surface images, and multiple internal images, e.g., but not limited to 96 internal images, with a focused scan step of e.g., but not limited to 0.25 mm or 0.3 mm.

[0073] In some cases, the hardware setup can include a camera base and a gemstone base, which allows imaging of any of the azimuth angle (φ), tilt angle (θ), and distance (d) information for each facet from the camera. This can be done by the computer sending instructions to each motor to move or rotate the camera and turn the pan-tilt head, as described herein. The wireframe information can be read to adjust the orientation and surface measurements. Surface measurements can include surface access to clarity features and surface polish features. Surface features can use specular reflection imaging, which uses diffused light for imaging the gemstone table and collimated light for imaging other facets. In some instances, the camera can be moved to an angle of about 45 degrees with respect to the facet and darkfield illumination can be used to measure the scattered image of inclusions when the camera views through the facet. This procedure can include focusing on the surface of the gemstone, selecting 16 azimuth angles (8 main pavilion images and 8 images between each pair of lower girdles), capturing 6 images from the surface to the interior at a scan step of 0.25 mm at each azimuth angle, and the scan step matching the depth of field of the lens. Then, in some instances, the camera is moved to other tilt angles to obtain internal images from the table.

[0074] In some embodiments, the hardware setup can include a pavilion side internal analysis setup. The system and method can be used to (a) rotate and scan the sample at different depths, (b) provide a magnification of ~2x to resolve ~3um needles and clouds, (c) use darkfield light or diffused backlight, (d) where the tilt angle for pavilion side imaging can be 20 to 50, while the tilt angle for girdle side imaging is close to 0, (e) and where darkfield light can improve the visibility of fine features such as clouds and needles, but may not show internal texture. In some instances, backlight can be used to image the texture inside or on the gemstone. Internal features can be imaged using darkfield light focused scanning.

[0075] Figure 2A is a side view of the example surface imaging camera 202 and the gemstone 210 on the pan-tilt head 206. In Figure 2A the example setup, the focal plane of the camera 202 is adjusted to be perpendicular or nearly perpendicular to a specific facet angle on the sample stone 210. As described, various motors and hardware configurations can be used to adjust the various angles and positions of the camera 202 relative to the stone 210 to capture multiple images of the gemstone 210. It should be noted that in some instances, the light source can move as the camera 202 is adjusted, as described.

[0076] Figure 12 Subsequently, more complex hardware arrangements are described, which can be used to capture images as more simply described in Figure 2A These two descriptions, either alone or in combination, describe the simple theory and more practical elements of the systems and methods for polar illumination and image capture described herein.

[0077] The output of the dimensional measurement can include the stone center coordinates and gem facet information. Example gem facet information can include ρ, θ, φ, which can be relative to the stone center coordinates. Figure 2B FIG. 200 is an example schematic diagram showing the output of the dimensional measurement. As Figure 2B shown, the coordinate plane can determine ρ, θ, and φ using angular measurements captured from the dimensional information.

[0078] The top-down view angle of capturing the gem table image shown in FIG. 1 and Figure 2A the side view angle shown in

[0079] For example, Figure 2A the oblique angle θ230 in Figure 2A can be adjusted by moving the camera 202 up and down 220 relative to the stone 210 and / or moving the pivot 221 to attempt to obtain an angle perpendicular to the facet of the gem 210 being imaged (e.g., the pavilion facet). The next angle is

[0080] the azimuth angle φ232 in Figure 2A which is adjusted by rotating or revolving the pan-tilt head 206 around the central pan-tilt axis so as to present each angle of the gem 210 to the camera 202 during rotation. Another coordinate variable is the distance d 224 from the camera 202 to the sample gem 210, which as described can be changed by moving the camera 202 into or out of 222 in the direction of the stone 210 by a motor. Figure 21 and Figure 22 All motors discussed with reference to

[0081] can communicate with a computer system as described inFigure 2A As shown in the example settings, to assist in analyzing each captured image, the parameters and / or coordinates of the hardware settings can be obtained, associated, and stored with each corresponding captured image. Such information can include, but is not limited to, the camera tilt angle θ230, the azimuth angle φ232, and the distance d224 from the camera 202 to the sample gemstone 210. This information can be obtained from sensors on various motors used to rotate the pan-tilt head 206, move the camera 202 outward and inward 222, up and down 220, and / or tilt 221 the camera 202. This information can be used to compare the hardware settings of various images taken under different lighting and camera parameters. As described, in some instances, the pan-tilt head 206 includes a vacuum assembly and ports for securing the sample 210 to the pan-tilt head 206 during evaluation. In some instances, the pan-tilt head 206 is smaller than the table of the gemstone 210 such that it does not obstruct images taken from the crown facets or at multiple angles.

[0082] In some instances, additionally or alternatively using the sensor data on the motors, wireframe data mapping the facets can be used to determine various lighting and camera parameters. For example, once the wireframe data of the gemstone 210 is determined and the distance 232 between the stone 210 and the camera 202 is determined, the wireframe data collected and determined for a single stone 210 can be used to map all the facets and junctions of the gemstone. As the azimuth angle 232 rotates, the camera 202 can view different facets, and a computer system can be used to determine the camera view angle for each image.

[0083] The alignment of the camera 200 can be along the vertical long axis of the camera. In some instances, the accuracy of the angular alignment of the azimuth and tilt angles can be between + / −0.6 degrees. In some instances, the accuracy of the angular alignment of the waist image can be between + / −0.5 degrees in azimuth. In some instances, the adjustment range of the tilt can be from +90 degrees to −75 degrees, and the azimuth is the full 360 degrees. Additional offsets can be set for each parameter to better reveal minor surface features in the image, such as the polishing features described herein.

[0084] In such an instance, the camera 202 can be mounted to a gimbal or motor arrangement to adjust the tilt angle θ230 of the camera with respect to the gemstone through computerized instructions. The azimuth angle φ232 can be adjusted by the motor rotating the pan-tilt head 206, while the gemstone 210 is placed or mounted on the pan-tilt head 206. Computer software can be used to send instructions to all the motorized pan-tilt heads, lighting, and camera imaging devices to automatically generate angle and distance parameters from the side-view camera or load information from the wireframe data, as described herein.

[0085] In this example, the three motorized gimbals can be adjusted and programmed for the tilt angle θ230, azimuth angle φ232, and distance d234 of camera 202 to move such that the system can sequentially capture images of gemstone 210. In this example, automatic shutter time control can even be used to avoid saturation and maximize the contrast of the images.

[0086] The adjustment and movement mechanisms of the camera and the light relative to the sample gemstone can be through servo motors, which are attached to gimbals, rods, supports, brackets, and other hardware architectures known in the industry. Gimbal 206 and / or camera 202 and light 204 can rotate relative to each other. Various other small motors, such as stepper motors, brushless motors, and brushed DC motors, can be used to move the camera and the light to change the tilt angle θ, azimuth angle φ, and the distance d from the camera to the gemstone, as described herein.

[0087] Figure 2C Another example of a similar azimuth angle hardware arrangement is shown Figure 2A as Figure 2C shown, motorized gimbal 250 for focus adjustment, motorized gimbal 252 for tilt adjustment, telecentric LED 254 for the wireframe, dark field LED 256, sample fixing nozzle 206 with vacuum, motorized gimbal 258 for azimuth angle adjustment, camera 202, relay optical system 260 including a polarizing mirror, imaging lens 262, telecentric LED 264 for surface analysis, polarizing mirror 266, telecentric lens 268 for wireframe capture, and camera 270 for wireframe capture. In this example, the motorized gimbal 250 for focus adjustment allows camera 202 to move and focus, as Figure 2A ,222 shown. The motorized gimbal 252 for tilt adjustment 252 allows camera 202 and imaging lens 262 to move, as Figure 2A ,221 shown. The telecentric LED 254 for the wireframe can be a light source, such as but not limited to an LED light source, for illuminating the sample on gimbal 206 for backlighting using the wireframe camera device 270 and lens 268 to obtain a silhouette image, where the gimbal motor 258 rotates gimbal 206, thus rotating any sample on the gimbal 360 degrees to capture images, as described herein. As described, gimbal 206 can include a suction or vacuum arrangement with a pump (not shown) to vacuum-fix the sample on gimbal 206 during rotation and imaging, but allowing for easy removal and replacement of the next sample. The telecentric LED 264 for surface analysis can include a polarizing mirror 266 for illuminating the sample surface. The dark field illumination arrangement 256 allows for low-angle illumination dark field illumination of the sample on gimbal 206 for surface analysis.

[0088] It should be noted that Figure 1A ,1B All of the motors, cameras, and light sources described in 2A and 2C can communicate with a computer arrangement capable of sending and receiving instructions and data between each motor and / or camera. In this way, the system can be automated, i.e., the motors, cameras, and lights are run by a computer and software executed by individual computer components, as described herein.

[0089] Examples of Image Analysis

[0090] Figure 3A-3B Figures 4A - 4C, 5A - 5B, 6A - 6B, 7A - 7B, and 8A - 8B show various examples of clarity features captured in images using the systems and methods described herein. These features can be depicted in images captured using the systems and methods described herein and then identified by a computer through image pixel analysis. As Figure 2A described, the faceting information collected during image capture can also be used to map these features. The system can then use these identified and mapped clarity features to determine an overall clarity grade, as described.

[0091] Figure 3A-3B is an illustration of example surface clarity features of a diamond. As Figure 3A-3B shown, the reflection can include maximum contrast for shallow surface features. This surface reflection image can be obtained using precise focusing and tilt alignment between the camera and the facet for image capture and analysis.

[0092] Figure 4A-4C shows various example surface clarity features. For example, Figure 4A depicts a scratch on the pavilion, Figure 4B shows a scratch on the table, and Figure 4C shows a feather on the pavilion.

[0093] Figure 5A-5B shows example table - side internal clarity features of a gemstone. As Figure 5A-5B shown, a feather (e.g., in Figure 5A ) or a pinpoint (e.g., in Figure 5B ) can include example internal clarity features.

[0094] Figure 6A-6B shows a bottom view of example pavilion / waist - side internal clarity features. As Figure 6A-6B shown, a feather or a needle - like (e.g., in Figure 6A ) or a chip and / or cloud - like (e.g., in Figure 6B ) can include example pavilion / waist internal clarity features.

[0095] Figure 7A-7BShows a pavilion view of an example pavilion / waisthand-side internal clarity feature with darkfield light. As Figure 7A-7B shown, reflection pairs or needles (e.g., in Figure 7A ) or feathers (e.g., in Figure 7B ) may include example pavilion / waisthand-side internal clarity features.

[0096] Figure 8A-8B Shows a pavilion view of an example pavilion / waisthand-side internal clarity feature with backlight. As Figure 8A-8B shown, textures (e.g., in Figure 8A ) or pinpoint (e.g., in Figure 8B ) may include example pavilion / waisthand internal clarity features.

[0097] Magnification and darkfield examples

[0098] In some examples, it may be difficult to capture a faceted image that clearly shows clarity features. Focused scanning using darkfield light can be used to image internal features. Darkfield light can be used at a lower angle of incidence to produce a darkfield image, except for surface anomalies. Thus, to improve spatial resolution while maintaining a sufficient field of view, the systems and methods herein can use magnification to improve image capture. In some examples, for a top view environment as shown in FIG. 1, the system can utilize a magnification of approximately 1.87x. In some examples, for side cameras as shown in Figure 2A and 2B , the system can utilize a magnification of approximately 2x. In some examples, a 1.1” sensor is used to cover a field of view of 7.07*5.18 (2x side camera) and 7.94*5.81 (1.87x top camera).

[0099] Figure 9A-9B Shows a diamond depicted at an increased lens magnification. For example, this can improve spatial resolution while maintaining a sufficient field of view.

[0100] In some examples, if darkfield illumination is used, features can be more clearly depicted in the captured image. Such darkfield illumination can make fine features in the captured image more clearly visible.

[0101] Figure 10A-10B Shows a diamond switched to darkfield light. Darkfield light can improve visibility, and it can also slightly magnify fine clarity features. In some cases, a Z-axis scan may be required to expand the sensing range. Internal features can be imaged using focused scanning with darkfield light.

[0102] Method examples

[0103] As described above, the systems and methods herein can be used to grade and identify high clarity diamonds, including diamonds of VVS and above, which account for approximately 28% of all diamonds. Figure 11 An example method step for using the system described herein to determine the clarity grade of a high clarity diamond is described.

[0104] At 1102, the method can include measuring internal clarity features on the table side (mostly VVS2 and some VVS1). This can be done using a high magnification imaging system with Z-axis scanning as shown in FIG. 1 and its description.

[0105] At 1104, the method can include first measuring surface features on the girdle side and then measuring internal features on the girdle side. This can be done using a high magnification imaging system with Z-axis scanning as shown in FIG. 1 and its description.

[0106] At 1106, the method can include measuring surface features on other facets. This can be done using Figure 2A the system shown in its description.

[0107] At 1108, the method can include measuring internal clarity features on the pavilion / girdle side (some VVS1). This can include imaging the pavilion / girdle with dark field / backlight. This can be done using Figure 2A the system shown in its description. In some cases, this may require a higher magnification than a reflection imaging camera. If necessary, the system can also measure internal features on the crown side.

[0108] Figure 11 The analysis of the internal and surface features of these method steps can be done by a computer using software that can analyze the digital pixelated images of the gemstone facets captured and any clarity features shown therein. Such image analysis can include boundary analysis, contrast pixel analysis, pixel counting, or any other type of pixel color or shade or contrast image analysis to locate, map, and then identify any clarity features. Such software can register any identified and / or mapped clarity features and assist in grading the gemstone clarity.

[0109] At 1110, if the diamond has no internal clarity features and only surface clarity features (IF), the method can include evaluating its surface clarity features using the previously collected data.

[0110] At 1112, if the diamond has no internal and surface clarity features, the computer software can evaluate the diamond as flawless.

[0111] If the diamond does have internal and / or surface clarity features, it can be compared to a threshold table describing various clarity grading limits to evaluate the diamond accordingly.

[0112] Automation of Diamond Facet Imaging

[0113] As described above for Figure 2A and Figure 12 the hardware arrangement, in many cases, the hardware design of the imaging system can adjust tilt and focus to achieve consistent gemstone imaging. However, sample alignment may not be easy. The alignment requirements can be angles of azimuth and tilt, and the focus can be approximately ±0.5° and ±0.2 mm respectively. In addition, the offset of sample positioning and the initial offset of the system also affect alignment. In many cases, even with hardware devices supporting angle and focus adjustment, it may take a long time (e.g., up to 1 hour) to correctly focus on each facet of a diamond. For this reason, software protocols can be created to automatically focus the camera on each facet.

[0114] In some instances, the systems and methods herein can be used to automatically capture facet images using a software protocol that, based on knowledge of diamond size information, an electric rotary stage, an electric tilt stage, and an electric linear translation stage, appropriately adjusts the azimuth, tilt, and focal length of the camera to automatically capture all facet information of the diamond (e.g., except for the table facet, which can be blocked by the stage / bracket and imaged using the hardware setup shown in FIG. 1). Such hardware is shown in Figure 2A and described in relevant paragraphs herein as well as in Figure 12 where details of the robotic movement of the camera and / or lighting are as described in Figure 13 , 14 , 15, 16, 17, 18, and 19. The systems and methods described herein can include system calibration and sample alignment strategies. The collected images can be used in various diamond evaluation systems, such as the systems described herein.

[0115] The imaging system described herein can automatically scan an entire diamond to image surface features and provide images for clarity evaluation. The entire process can be automated, and the imaging system can provide consistent grading results.

[0116] For example, the systems and methods herein can be used to calculate the requirements for adjusting azimuth and tilt rotation and focus translation in order to automatically focus on each diamond facet in sequence based on input information such as gemstone size information. The systems and methods herein can be used to compensate for any system calibration errors, such as a mismatch in distance or tilt between the designed and assembled final hardware setup. The systems and methods herein can be used to compensate for any gemstone positioning errors, such as a mismatch between the center of the gemstone and the center of the system rotation center (on the rotary stage). The systems and methods herein can be used to determine the focus quality of an image based on computer feedback on the captured image, which provides a feedback loop to the camera to adjust the focus of the system.

[0117] In some instances, the system can use different designs to automate image capture, illumination, and gemstone rotation. For example, such a design can include the device continuously rotating and tilting the sample, using a laser as an illumination source to shine on the sample gemstone, and using a camera to capture images. During the rotation and tilting of the sample gemstone, when the angle between the laser and the camera is the same, each facet will form a specular reflection of the laser spot. Each formed specular reflection of the laser spot can represent a facet on the sample gemstone or diamond. As described herein, the orientation of the sample gemstone, such as the angle of the rotating turntable, can be recorded. The system can adjust the sample gemstone to these angles and focus the camera to capture images of the diamond gemstone surface. In some non-limiting instances, for a common round cut diamond with 56 facets plus 1 table, scanning and focusing may take approximately 15 minutes.

[0118] This instance can provide a method for converting gemstone size information into azimuth, inclination, and distance information, and accordingly adjusting the electric pan-tilt head for surface imaging. In addition, the calibration method can consider the deviation between the design and the actual system alignment. The calibration process can be used to compensate for the deviation. In addition, additional conversions can be performed to compensate for the offset caused by the gemstone geometry. This method can automatically capture the reflected images of each facet of the diamond.

[0119] This instance can be used for various applications. For example, the method described herein can automatically detect gemstone surface features or identify diamond surface polishing or clarity features. In addition, the method described herein can collect clarity feature images for clarity grading or detecting potential surface treatments, such as burn marks caused by laser drilling or high-pressure high-temperature treatment.

[0120] Figure 12 The example shown depicts the hardware setup of a system for capturing gemstone size information, converting the gemstone size information into azimuth, inclination, and distance information, and accordingly adjusting the electric pan-tilt head for surface imaging. This arrangement depicts practical hardware elements that can be used to capture images of polar coordinate positioning, similar to Figure 2A the simplified arrangement of Figure 12 As shown, the system 1200 can include any one of a side camera 1202, a telecentric LED 1204, a size measurement camera 1206, a focus adjustment subsystem 1208, an inclination adjustment subsystem 1210, and an azimuth adjustment subsystem 1212. The pan-tilt head 1240 on which the gemstone can be placed or vacuum-attached (table side down or up) can communicate with a main shaft or a part thereof that is rotated or turned by an azimuth rotation motor 1242. As described herein, by rotating the gemstone pan-tilt head, and thus rotating the gemstone sample through 360 degrees of azimuth, various cameras can then capture images of the gemstone facets.

[0121] In some instances, the dimensional measurement camera 1206 can capture the dimensions of a gemstone placed in the system 1200 and backlit by the backlighting system 1230. Additionally, the focus adjustment subsystem 1208 can manipulate the side camera 1202 and the telecentric LED 1204 configured to capture a side view of the gemstone to modify the focus of the system 1200 when capturing an image of the gemstone. The tilt adjustment subsystem 1210 and the azimuth adjustment subsystem 1212 can adjust the system 1200 to capture the azimuth (φ), tilt angle (θ), and distance (d) information of each facet of the gemstone. In Figure 12 instances, the various adjustment components can be moved by motors that communicate with one or more computers, as described herein. In such instances, the computer system can send instructions to move the robotic assembly about a pivot to move and adjust the various cameras and / or lighting sources, as described herein. For example, the tilt adjustment 1210 system can be a motor for moving the robotic arm on which the side camera 1202 is mounted to adjust the tilt angle of the coordinates for image capture, as described herein. For example, the azimuth adjustment 1212 can be a motor for rotating the gimbal on which the sample gemstone is placed to change the azimuth of the side camera 1202 relative to the gemstone.

[0122] Figure 12 The system 1200 in can capture the azimuth of each facet of the gemstone, the tilt angle (θ), and any one of the distance (d) information. Additionally, the wireframe / dimensional information can be read to adjust the orientation of the gemstone. Further, this information can be used for surface polish measurement. For example, the side camera tilt azimuth can be between +90° and -75°, and the azimuth angle is approximately 360°. In some cases, the systems described herein can use Figure 2A the gemstone 210 on the camera 202 and the gimbal 206 described in to perform surface imaging.

[0123] Image Analysis and Grade Determination

[0124] As described, various surface and internal images of a sample gemstone can be taken using the methods and systems described herein. In an instance, the computer system can analyze these digital images and generate a clarity grade therefrom.

[0125] For surface analysis, in some instances, this can include data analysis of surface feature images. In such instances, the computer can locate surfaces and surface-reaching features from specular reflection images of each facet. In some instances, this can be achieved through boundary analysis or contrast comparison of pixels within each image. In some instances, the computer can then identify the types of surfaces and surface-reaching features in the image. For example, the image may show anomalous inclusions such as, but not limited to, feathers, pits, scratches, polish lines, surface texture, burns, or others. Next, the computer can classify the extent of the surfaces and surface-reaching features based on the size and contrast of the features. Such classification can be the computer comparing the size and / or contrast of the detected inclusions with previously determined thresholds. In some instances, such classification performed by the computer can use a look-up table or chart. In some instances, artificial intelligence can be used to compare the detected inclusions to determine the classification of each inclusion.

[0126] For internal analysis, in some instances, the computer can locate internal and surface-reaching internal features from captured scattered digital images at different azimuth angles and depths. In such instances, the combination of azimuth angle and depth can be considered by the computer as different perspectives to assist in the location of features within the gemstone. Then, the computer can identify the types of internal and surface-reaching internal features such as, but not limited to, feathers, needles, clouds, internal texture, or other inclusion types. Then, the computer can use the information from the surface analysis to distinguish between inclusion-only and other features, where inclusion-only features do not appear on the gemstone surface. Next, the computer can classify the extent of the internal and surface-reaching internal features based on the size and contrast of the features. Such classification can be the computer comparing the size and / or contrast of the detected inclusions with previously determined thresholds. In some instances, such classification performed by the computer can use a look-up table or chart. In some instances, artificial intelligence can be used to compare the detected inclusions to determine the classification of each inclusion.

[0127] In some instances, once the classification and quantity of inclusions in the gemstone surface and internal regions are determined, this information can be used to generate an overall clarity grade for the gemstone. Similarly, such analysis can include the computer using a look-up table, chart comparison, artificial intelligence analysis, or other diagnostics.

[0128] Additionally or alternatively, any inclusions detected by the systems and methods herein can be stored for fingerprint type matching. In such instances, the location and mapping of surface and / or internal inclusions can be stored and compared to later measured gemstones for matching and identification purposes. In some instances, such mapping information can be printed and presented to the user. In some instances, a certificate with the grade and mapped inclusions can be generated for the analyzed gemstone.

[0129] Camera Axis Calibration

[0130] Figure 13 、 14 and 15 depict various calibration arrangements that can be used with the systems and methods herein to calibrate the camera angle for capturing images of gemstone facets for analysis. This calibration is very useful for maintaining accurate facet counting and identification and improving the focus of the images. Example calibrations can include the arm rotation axis, such as the tilt adjustment center relative to the gimbal rotation center position. The arrangement of the camera and the gimbal can involve any of the settings described herein, including but not limited to those described in FIGS. 1, Figure 2A and Figure 12 .

[0131] Figure 13 and Figure 14 illustrate example configurations 1300 and 1400 for arm axis calibration in the X direction. Additionally, Figure 15 illustrates configuration 1500 for arm axis calibration in the Z direction.

[0132] For example, in Figure 13 , configuration 1300 can include a camera 1302 placed at a distance D0 1310 above the gimbal 1304. As another example, in Figure 14 , for configuration 1430, the distance D1 between the inner edge of the gimbal 1404 and the camera 1402. Additionally, the distance D3 1440 can include the distance between the center of the gimbal 1404 and the inner edge of the camera 1402. The gimbal 1404 can include a diameter D2 and a radius D 1450.

[0133] Viewed from the Z direction, as Figure 15 illustrates, configuration 1500 can include a height H 1508 above the gimbal, a height H1 1510 of the gimbal, and a height H0 1520 (H1) of the gimbal and the height (H) above the gimbal.

[0134] Each description of moving the camera and / or the gimbal can include sending commands from the computer described herein to a motor communicating with the motor to move the hardware described herein. By moving the motor of the camera and / or the gimbal, each hardware component can be moved relative to each other to reach the desired position, as described herein.

[0135] As Figure 13 illustrates, the arm axis calibration process can include setting the camera 1302 home position to a position where the camera viewing axis is perpendicular to the plane of the gimbal 1304. From this position, the distance D0 1310 between the camera and the gimbal can be measured.

[0136] As Figure 14As shown, the process may further include rotating the camera 1402 by about 90 degrees and / or using a second camera position on the side of the pan-tilt head 1404, and then measuring the distance D3 1440 between the camera and the rotation center of the pan-tilt head by measuring the distance D1 1430 between the camera and the edge of the pan-tilt head and the diameter D2 or twice the radius D 1450 of the pan-tilt head. In such an instance, the camera 1402 may have a fixed focal plane / working distance. This distance between the camera and the pan-tilt head can be adjusted to maximize the clarity of the image of the edge of the pan-tilt head. The distance between the edge 1404 of the pan-tilt head and the camera 1402 may be equal to the working distance D11430 of the camera.

[0137] In some cases, as Figure 13-14 shown, the offset of the center of the pan-tilt head rotating axially in the X-axis direction of the arm may be D = D0 - (D1 + 0.5 * D2). As Figure 15 shown, the offset of the surface of the pan-tilt head axially in the Z-axis vertical direction of the arm can be performed by rotating the arm 90 degrees from the original position or using a second camera arranged on the side of the pan-tilt head, capturing an image of the pan-tilt head, and calculating the height H 1508 = H0 1520 - H1 1510 of the pan-tilt head relative to the center of the image.

[0138] Surface reflection capture

[0139] In high-purity grading, surface reflection images can be very useful. To capture such surface reflection images, a surface reflection capture process can be performed based on various faceting types on different cut stones. For example, for round brilliant cut (RBC) diamonds, faceting capture can be carried out in the following order: (1) pavilion main face, (2) lower girdle, (3) upper girdle, (4) bezel, (5) star face. To capture such reflection images, the robotic arm can move around the pan-tilt head and the sample gemstone using calibration routines and positioning instructions to capture surface reflection images for analysis and / or storage.

[0140] Before surface reflection capture, the camera with the robotic arm position can be in the origin position, which can be perpendicular to the pan-tilt head, with the defined θ value being 0. The robotic arm can rotate around axis A in the XY plane. Based on the faceting information: ρ, θ, and φ, the stone center, and the calibrated axis A position, three steps can be required to be completed before capturing the image. (Note Figure 16 that the coordinate plane in

[0141] Figure 16 is a schematic diagram 1600 of an example of the coordinate plane for surface reflection capture. As Figure 16 shown, S1610 can specify the stone center, and A1612 can specify the rotation axis of the camera arm 1620, which can be parallel to the Z axis.

[0142] As part of the process of performing surface reflection capture, the gimbal can rotate based on the facet azimuth angle θ value and the tilt value φ. When the arm rotates from the pavilion side to the crown side, the angle between the lens and the light projected onto the gimbal plane changes. The geometric figure describing the angle change can be specified as:

[0143] θ = Atan(Dx / Dz).

[0144] When the camera arm rotates, Dx (the distance between the lens and the light on the gimbal plane) can remain constant, and Dz (the distance from the lens to the rotation axis) can change according to the facet tilt angle φ.

[0145] Figure 17 is a schematic diagram 1700 of an example coordinate plane for rotating the camera arm, which can be used in the systems and methods described herein to illuminate and / or capture images of gemstones. The surface reflection capture process can also include rotating the camera arm based on the facet tilt angle φ. Additionally, the surface reflection capture process can include focusing the camera based on facet information ρ, θ, φ, the stone center, and the arm rotation axis position.

[0146] Figure 18 is a schematic diagram 1800 of an example for focus adjustment based on a known or pre-loaded gemstone wireframe model. The distance D from the camera lens to the arm rotation axis is D = Da + R + WD, where Da is the adjusted distance, R is the distance ρ from the stone center to the facet, and WD is the lens working distance. Based on the geometric relationship between the arm axis and the stone center Da = Das*cos(θ), Das can be the distance between the camera arm axis and the stone center, θ = θ1 + θ2; θ1 = 90 - φ, φ is the facet tilt angle, and θ2 can be the tilt angle of the line connecting the arm axis and the stone center.

[0147] Figure 19 is a schematic diagram 1900 of an example of wireframe geometric relationships. The surface reflection capture process can also include optimizing focus through Z-scanning.

[0148] Figure 20 is a process 2000 of an example workflow for converting gemstone size information into azimuth, tilt, and distance information and adjusting the electric gimbal accordingly for surface imaging. At 2002, the process can include calibrating the arm axis of the system.

[0149] The arm axis calibration relies on the feedback of the silhouette image of camera 1206 and the image of nozzle 1240 of side camera 1202. First, a series of silhouette images of the gimbal nozzle are taken to confirm that the upper surface of the gimbal nozzle is flat during nozzle rotation. Then, side camera 1202 is adjusted to image the gimbal nozzle. When camera 1202 is perpendicular to the gimbal nozzle, the area size of the nozzle plane is the largest.

[0150] At 2004, the process can include placing a gemstone sample on a turntable to capture gemstone size information. This can include performing dimensional measurements using silhouette imaging techniques. This can also include loading dimensional information from another measurement system. Additionally, two or three facets can be identified by scanning. The scan can locate these facets based on the relative azimuth angle and the slope difference. Based on the known facets, the offset between the sample center and the turntable rotation center can be calculated. The known facets can be projected into the dimensional data, and other facets can be estimated.

[0151] At 2006, the process can include sequentially measuring the surface reflections from all the facets. This can include rotating the turntable based on the facet azimuth angle θ value and the slope value φ. This also includes adjusting the angular offset based on the geometry. This also includes focusing the camera based on the facet information ρ, θ, φ, the gemstone center, and the arm rotation axis position. This can also include any one of applying an additional offset based on the geometric relationship, scanning the camera to optimize the focus, and / or capturing an image of the surface specular reflection.

[0152] In an example implementation, a method is provided for converting gemstone size information into various information types and modifying an electric turntable for surface imaging. In some cases, the method can include performing a calibration process on the axis of the arm connected to the camera, the axis of the arm being relative to the turntable. In some cases, the calibration process is at least based on the offset between the target alignment and the actual alignment of the arm.

[0153] The method can also include determining a set of size information of the gemstone on the turntable. The set of size information can be determined based on a silhouette imaging process. Determining the set of size information can include obtaining the set of size information from a measurement system. In some cases, determining the set of size information can include calculating the offset between the gemstone center and the turntable rotation center.

[0154] The method can also include using the set of size information to identify one or more facets of the gemstone. In some cases, identifying one or more facets includes identifying two or three facets of the gemstone based on the relative azimuth angle and the slope difference.

[0155] The method can also include measuring a dataset of surface reflections from each identified facet. In some cases, measuring the dataset of surface reflections further includes rotating the turntable based on the facet azimuth angle θ value and the slope value φ value.

[0156] In some cases, measuring the dataset of surface reflections further includes adjusting the angular offset based on the defined geometry of the gemstone.

[0157] In some cases, measuring the dataset of surface reflections further includes focusing the camera based on any one of ρ, θ, φ, the gemstone center, and the arm rotation axis position.

[0158] In some cases, the measured surface reflection data set further includes applying an additional offset based on the geometric relationship of the gemstone.

[0159] In some cases, the measured surface reflection data set further includes performing a scanning process on the camera to optimize the focus of the camera.

[0160] In some cases, the measured surface reflection data set further includes capturing a specular reflection image of the surface of the gemstone.

[0161] The method may further include adjusting the position of the pan-tilt head based on the surface reflection data set for imaging the gemstone surface.

[0162] In some cases, the method further includes projecting each of one or more facets onto a dimensional information set to estimate the position of each other facet of the gemstone.

[0163] Network instance

[0164] Figure 21 Instances of networked computing arrangements that can be utilized herein are shown. In Figure 21 , a computer 2102 for processing images from a camera (142 in FIG. 1) can generate data including pixel data of the captured images. The computer 2102 can be any number of computer types, alone or in combination, such as those included with the camera itself, the light source itself, and / or another computer arrangement that communicates with the camera and / or optical computer components and in some instances with the pan-tilt head motor and / or the camera lens motor, including but not limited to laptops, desktops, tablets, phablets, smartphones, or any other type of device for processing and transmitting digital data. Such a computer 2102 can be used to control the camera 2180 and / or the light generation device 2190 as described herein. Additional or alternative examples of the computer 2102 are shown in FIG. 8.

[0165] Return to Figure 21, computer resources in any aspect of the system can reside in a networked or distributed format via network 2120. Additionally, pixelated image data captured from any computer 2102 can be transmitted to backend computer 2130 and associated data storage 2132 for storage and analysis. In some instances, the transmission can be wireless via cellular or WiFi transmission with associated routers and hubs 2110. In some instances, the transmission can be via a wired connection 2112. In some instances, the transmission can reach backend server computer 2130 and associated data storage 2132 via a network such as the Internet 2120. At backend server computer 2130 and associated data storage 2132, the pixelated image data can be stored, analyzed, compared with previously stored image data for matching, or any other type of image data analysis can be performed. In some instances, the storage, analysis, and / or processing of the image data can be done on the computer 2102 involved in the original image capture. In some instances, the data storage, analysis, and / or processing can be shared between local computer 2102 and backend computing system 2130. The networked computer resources 2130 can utilize stronger data processing capabilities than local computer 2102. In this way, the processing and / or storage of the image data can be offloaded to the computing resources available on the network. In some instances, the networked computer resources 2130 can be virtual machines in a cloud infrastructure. In some instances, the networked computer resources 2130 can be distributed across multiple computer resources via a cloud infrastructure. The instance of a single computer server 2130 is not intended to be limiting and is merely one example of the computing resources that can be utilized by the systems and methods described herein.

[0166] Example computer device

[0167] As described, any number of computing devices can be arranged within or connected to the various component parts of the systems described herein, and / or used to implement the methods described herein. For example, a camera system can include its own computing system, a lighting system can include its own computing system, and data from camera images can be collected, stored, and analyzed using a computing system. In some instances, some computing resources can be networked or communicate via a network such that they need not be co-located with the optical systems described herein. In any case, any computing system used herein can include Figure 22 the component parts described.

[0168] Figure 22An example computing device 2200 that can be used in the systems and methods described herein is shown. In the example computer 2200, a CPU or processor 2210 communicates with a user interface 2214 via a bus or other communication means 2212. The user interface includes example input devices such as a keyboard, mouse, touch screen, buttons, joystick, or other user input devices. The user interface 2214 also includes a display device 2218, such as a screen. Figure 22 The computing device 2200 shown in Figure 22 also includes a network interface 2220 that communicates with the CPU 2220 and other components. The network interface 2220 can allow the computing device 2200 to communicate with other computers, databases, networks, user devices, or any other computing-capable device. In some examples, the communication method can be via WiFi, cellular, low-power Bluetooth, wired communication, or any other communication means. In some examples, the example computing device 2200 includes peripherals 2224 that also communicate with the processor 2210. In some examples, the peripherals include an antenna 2226 for communication. In some examples, the peripherals 2224 can include a camera device 2228. In some examples, the memory 2222 of the computing device 2200 communicates with the processor 2210. In some examples, the memory 2222 can include instructions for executing software, such as an operating system 2232, a network communication module 2234, other instructions 2236, application programs 2238, an application program for digitizing images 2240, an application program for processing image pixels 2242, data storage 2258, data such as data tables 2260, transaction logs 2262, sample data 2264, encrypted data 2270, or any other type of data.

[0169] Conclusion

[0170] As disclosed herein, implementations consistent with this embodiment can be implemented by computer hardware, software, and / or firmware. For example, the systems and methods disclosed herein can be implemented in various forms, including, for example, a data processor, such as a computer that also includes a database, digital electronic circuitry, firmware, software, a computer network, a server, or combinations thereof. Additionally, while some disclosed implementations describe specific hardware components, the systems and methods consistent with the innovations herein can be implemented by any combination of hardware, software, and / or firmware. Further, the above aspects and principles of the innovations herein can be implemented in a variety of environments. Such environments and related applications can be specifically constructed to execute various routines, processes, and / or operations according to an embodiment, or they can include a general-purpose computer or computing platform that is selectively activated or reconfigured by code to provide the necessary functionality. The processes disclosed herein have no inherent connection to any particular computer, network, architecture, environment, or other device and can be implemented by a suitable combination of hardware, software, and / or firmware. For example, various general-purpose machines can be used with programs written according to the teachings of this embodiment, or it may be more convenient to construct a specialized apparatus or system to implement the required methods and techniques.

[0171] Aspects of the methods and systems described herein (such as logic) can be implemented as the functionality programmed into any one of a variety of circuits, including programmable logic devices ("PLDs"), such as field-programmable gate arrays ("FPGAs"), programmable array logic ("PAL") devices, electrically programmable logic and storage devices, standard cell devices, and application-specific integrated circuits. Other possibilities for implementing the aspects include: storage devices, microcontrollers with memory (such as EEPROM), embedded microprocessors, firmware, software, etc. Additionally, the aspects can be implemented in a microprocessor with software-based circuit simulation, discrete logic (sequential and combinational), custom devices, fuzzy (neural) logic, quantum devices, and hybrids of any of the above device types. The underlying device technology can employ a variety of element types, for example, metal-oxide semiconductor field-effect transistor ("MOSFET") technologies such as complementary metal-oxide semiconductor (CMOS), bipolar technologies such as emitter-coupled logic ("ECL"), polymer technologies (e.g., silicon-conjugated polymers and metal-conjugated polymer-metal structures), analog and digital hybrids, etc.

[0172] It should also be noted that, in terms of their behavior, register transfer, logic components, and / or other features, the various logics and / or functions disclosed herein can be implemented using any number of combinations of hardware, firmware, and / or as data and / or instructions embodied in various machine-readable or computer-readable media. Computer-readable media in which such formatted data and / or instructions can be implemented include, but are not limited to, various forms of non-volatile storage media (e.g., optical, magnetic, or semiconductor storage media) and carrier waves that can be used to transmit such formatted data and / or instructions via wireless, optical, or wired signal media or any combination thereof. Examples of transmitting such formatted data and / or instructions via carrier waves include, but are not limited to, transmission (uploading, downloading, emailing, etc.) over the Internet and / or other computer networks via one or more data transfer protocols (e.g., HTTP, FTP, SMTP, etc.).

[0173] Unless the context clearly requires otherwise, throughout the description and claims, the words "comprise", "comprising", etc. shall be construed in an inclusive sense, rather than an exclusive or exhaustive sense; that is, they shall be construed as "including, but not limited to". The use of the singular or plural words also includes the plural or singular respectively. In addition, the words "herein", "hereunder", "above", "below", and words of similar import refer to the whole of this application, and not to any particular part of this application. When the word "or" is used to refer to a list of two or more items, the word covers all of the following interpretations of the word: any item in the list, all items in the list, and any combination of items in the list.

[0174] Although certain presently preferred embodiments have been specifically described herein, it will be apparent to those skilled in the art of the technology described in this description that various changes and modifications can be made to the various embodiments shown and described herein without departing from the spirit and scope of this embodiment. Therefore, the embodiments of the present invention are limited only to the extent required by the rules of applicable law.

[0175] The present embodiment can be embodied in the form of methods and apparatuses for implementing these methods. The present embodiment can also be embodied in the form of program code embodied in a tangible medium, such as a floppy disk, a CD-ROM, a hard disk, or any other machine-readable storage medium, wherein, when the program code is loaded into a machine (such as a computer) and executed by the machine, the machine becomes an apparatus for implementing the present embodiment. The present embodiment can also be in the form of program code, for example, whether stored in a storage medium, loaded into a machine and / or executed by a machine, or transmitted through some transmission medium, such as through wires or cables, through optical fibers, or through electromagnetic radiation, wherein, when the program code is loaded into a machine (such as a computer) and executed by the machine, the machine becomes an apparatus for implementing the present embodiment. When executed on a general-purpose processor, the program code segments combine with the processor to provide a unique apparatus similar to the operation of a specific logic circuit.

[0176] Software is stored in a machine-readable medium, which can have various forms, including but not limited to tangible storage media, carrier media, or physical transmission media. For example, non-volatile storage media include optical discs or magnetic disks, such as any storage device in any computer or similar device. Volatile storage media include dynamic memories, such as the main memory of a computer platform. Tangible transmission media include coaxial cables, copper wires, and optical fibers, including the wires that make up the internal bus of a computer system. The form of carrier transmission media can be an electrical signal or an electromagnetic signal, or it can be a sound wave or a light wave, such as the sound wave or light wave generated during radio frequency (RF) and infrared (IR) data communication processes. Therefore, common forms of computer-readable media include: magnetic disks (e.g., hard disks, floppy disks, flexible disks) or any other magnetic medium, CD-ROMs, DVDs or DVD-ROMs, any other optical medium, any other physical storage medium, RAM, PROM, and EPROM, FLASH-EPROM, any other storage chip, a carrier wave for transmitting data or instructions, a cable or link for transmitting such carrier waves, or any other medium from which a computer can read program code and / or data. Many of these forms of computer-readable media can involve transmitting one or more instruction sequences to a processor for execution.

[0177] The above description for purposes of explanation has been described with reference to specific embodiments. However, the above illustrative discussion is not intended to be exhaustive, nor is it intended to limit the embodiments to the precise forms disclosed. Given the above teachings, many modifications and variations are possible. The selected and described embodiments are chosen to best explain the principles of the embodiments and their practical applications, so that others skilled in the art can best utilize the various embodiments and make various suitable modifications according to the particular uses contemplated.

Claims

1. A method, comprising, by a computer communicating with at least one light source and a digital camera, irradiating the table of a sample diamond with diffused light; by the computer, causing the digital camera to capture a surface image of the diamond table under the diffused light; by the computer, irradiating the facets of the sample diamond other than the table with collimated light; by the computer, causing the digital camera to capture a surface image of the diamond facets other than the table under the collimated light; by the computer, illuminating the table of the sample diamond with darkfield illumination; by the computer, causing the digital camera to capture internal images of the diamond table at multiple depths of focus under the darkfield illumination; by the computer, causing the digital camera to capture internal images of the diamond taken through the facets other than the table at multiple depths of focus under the darkfield illumination.

2. The method according to claim 1, further comprising, by the computer, analyzing the captured surface digital images of the diamond table and the surface digital images of the diamond facets other than the table to detect anomalies.

3. The method according to claim 2, further comprising, by the computer, analyzing the captured internal digital images of the diamond table and the internal digital images of the diamond taken through the surface of the diamond facets other than the table to detect anomalies.

4. The method according to claim 3, further comprising, by the computer, assigning a clarity grade to the sample diamond based on the analyzed surface digital images of the diamond table, the surface digital images of the diamond facets other than the table, the internal digital images of the diamond table, and the internal digital images of the diamond taken through the diamond facets other than the table.

5. The method according to claim 1, wherein the multiple internal images are taken with a focusing scan step of 0.3 mm.

6. The method according to claim 1, wherein, under collimated light, the captured digital camera images of the surface of the diamond facets other than the table include capturing images at 16 different azimuth angles.

7. The method according to claim 6, wherein, under collimated light, the captured digital camera images of the surface of the diamond facets other than the table include 56 surface images.

8. The method according to claim 6, wherein the captured digital camera images of the internal images include 96 internal images with a focusing scan step of, for example but not limited to, 0.25 mm or 0.3 mm.

9. The method according to claim 1, further comprising, by the computer, analyzing the surface images by using boundary analysis or contrast comparison of pixels within each image to locate surface and surface arrival features from the surface images of each facet; by the computer, identifying the types of surface and surface arrival features in the images, wherein the types include feathers, pits, scratches, polish lines, surface texture, or burns; Through the computer, classify the surface and the degree of surface-reaching features based on the size and contrast of the surface features by comparing the detected inclusion size and contrast with previously determined thresholds; Through the computer, analyze the internal image by locating internal and surface-reaching internal features from the captured internal digital images at different azimuth angles and depths; Through the computer, identify the types of internal and surface-reaching internal features, where the types include feathers, needles, clouds, or internal textures; Through the computer, distinguish internal inclusions using surface analysis; Through the computer, classify the degree of internal and surface-reaching internal features based on the size and contrast of the internal features, using pixel counting and contrast; Through the computer, generate a clarity grade using surface and internal analysis.

10. A method, comprising: Using the camera tilt angle θ230, azimuth angle φ, and the distance d from the camera to the gemstone, determine a set of size information of the gemstone on the turntable; Using the set of size information to identify one or more facets of the gemstone; Measure a set of surface reflection data from each identified facet; and Based on the set of surface reflection data, adjust the position of the turntable to image the gemstone surface.

11. The method according to claim 10, further comprising performing a calibration process on the axis of the arm connected to the camera, the axis of the arm being relative to the turntable.

12. The method according to claim 11, wherein the calibration process is at least based on the offset between the target alignment and the actual alignment of the arm.

13. The method according to claim 10, wherein the set of size information is determined based on a silhouette imaging process of the gemstone using backlighting.

14. The method according to claim 10, wherein determining the set of size information includes obtaining the set of size information from a measurement system.

15. The method according to claim 10, wherein identifying the one or more facets includes identifying two or three facets of the gemstone based on the relative azimuth angle and slope difference.

16. The method according to claim 10, wherein determining the set of size information includes calculating the offset between the center of the gemstone and the rotation center of the turntable.

17. The method according to claim 10, wherein the method further comprises: Project each of the one or more facets onto the set of size information to estimate the positions of each other facet of the gemstone.

18. The method according to claim 10, wherein measuring the set of surface reflection data further includes rotating the turntable based on the facet azimuth angle θ value and slope value φ value.

19. The method according to claim 10, wherein measuring the set of surface reflection data further includes adjusting the angular offset based on the defined geometry of the gemstone.

20. The method according to claim 10, wherein measuring the set of surface reflection data further includes focusing the camera based on any one of ρ, θ, φ, the gemstone center, and the arm rotation axis position.

21. The method according to claim 10, wherein measuring the surface reflection data set further comprises applying an additional offset based on the geometric relationship of the gemstone.

22. The method according to claim 10, wherein measuring the surface reflection data set further comprises performing a scanning process on the camera to optimize the focus of the camera.

23. The method according to claim 10, wherein measuring the surface reflection data set further comprises capturing a specular reflection image of the surface of the gemstone.

24. A method for capturing an image on a gemstone to determine a clarity grade, the method comprising: obtaining a wireframe model of the gemstone by a computer in communication with a digital camera, wherein the gemstone is on a turntable; using the wireframe model by the computer to calculate the azimuth angle (φ), the tilt angle (θ), and the distance (d) from the camera to each facet of the gemstone; sending instructions by the computer to a turntable motor, a tilt motor, and a focus adjustment motor, the turntable motor being configured to rotate the turntable, the tilt motor being configured to adjust the tilt of the camera with respect to the turntable, and the focus adjustment motor being configured to adjust the focus of the camera with respect to the turntable; and sending instructions to the camera and a light source to illuminate the turntable and the gemstone and sequentially capture images of each facet of the gemstone; adjusting, by the computer, the tilt motor to move the camera to an angle of approximately 45 degrees with respect to a first facet, illuminating the gemstone with a dark field light source, and capturing dark field images of each facet of the gemstone.

25. The method according to claim 24, wherein obtaining the wireframe model comprises rotating, by the computer in communication with the turntable motor, the turntable together with the gemstone and capturing silhouette images of the gemstone by the digital camera at multiple rotation angles to generate the wireframe model of the gemstone.

26. The method according to claim 24, wherein the number of captured images comprises sixteen azimuth angles, including eight pavilion main images and eight images between each pair of lower girdles.

27. The method according to claim 26, wherein at each azimuth angle, six images are captured from the surface to the interior of the gemstone by the computer.

28. The method according to claim 27, wherein the internal imaging scan step of the six images is 0.25 mm.

29. The method according to claim 28, wherein the scan step matches the depth of field of the lens.

30. The method according to claim 29, further comprising moving, by the computer, the camera to an additional tilt angle to obtain internal images from the table side of the gemstone.

31. A system comprising: A computer with a processor and a memory, which communicates with at least one light source and a digital camera, the computer being configured to illuminate a sample diamond table with diffused light, wherein the sample diamond is configured on a turntable such that the digital camera captures a surface image of the diamond table under the diffused light, illuminate the facets of the sample diamond other than the table with collimated light such that the digital camera captures a surface image of the diamond facets other than the table under the collimated light, illuminate the sample diamond table with dark field illumination such that the digital camera captures internal images of the diamond table at multiple focal depths under the dark field illumination, and cause the digital camera to capture internal images of the diamond facets other than the table at multiple focal depths under the dark field illumination.

32. The system according to claim 31, wherein the system further comprises a turntable motor configured to rotate the turntable, an inclination motor configured to adjust the inclination of the digital camera with respect to the turntable, and a focus adjustment motor configured to adjust the focus of the digital camera with respect to the turntable.

33. The system according to claim 32, wherein the system further comprises a back silhouette light source and a silhouette camera, the silhouette camera being configured to capture a plurality of digital silhouette images of the sample gemstone on the rotating turntable.

34. The system according to claim 31, wherein the computer is further configured to analyze the surface image by locating surface and surface-reaching features from the surface image of each facet by using boundary analysis or contrast comparison of pixels within each image; identifying the types of surface and surface-reaching features in the image, wherein the types include feathers, pits, scratches, polish lines, surface texture or burns; classifying the degree of surface and surface-reaching features based on the size and contrast of the surface features by comparing the detected inclusion size and contrast with previously determined thresholds; analyzing the internal image by locating internal and surface-reaching internal features from the captured internal digital images at different azimuth angles and depths; identifying the types of internal and surface-reaching internal features, wherein the types include feathers, needles, clouds or internal texture; distinguishing internal inclusions by using surface analysis; classifying the degree of internal and surface-reaching internal features by using pixel counting and contrast based on the size and contrast of the internal features; and generating a clarity grade by using surface and internal analysis.

Images