Apparatus and method for analyzing matter of an object

Abstract

Provided are an apparatus and method for analyzing a substance of an object. An apparatus for analyzing a substance of an object includes a sensor portion including an image sensor and a plurality of light sources disposed around the image sensor, and a processor configured to drive the plurality of light sources to obtain absorbance of each pixel based on intensity of light received by each pixel of the image sensor, correct the absorbance of each pixel based on a distance between the plurality of light sources and each pixel, and analyze the substance of the object based on the corrected absorbance of each pixel.

Description

[0001] This application claims priority to Korean Patent Application No. 10-2020-0077783, filed on June 25, 2020, with the Korean Intellectual Property Office, the entire disclosure of which is incorporated herein by reference for all purposes. Technical Field

[0002] The disclosed embodiments relate to apparatus and methods for analyzing the material of an object using a complementary metal-oxide-semiconductor (CMOS) image sensor. Background Technology

[0003] Antioxidants play a crucial role in scavenging harmful free radicals, thus protecting skin from aging and maintaining overall health. A typical example of an antioxidant is carotenoids, and non-invasive methods for measuring carotenoids have been investigated. Raman spectroscopy and absorbance-based methods are commonly used to measure antioxidant signals. Raman spectroscopy offers high accuracy but suffers from drawbacks such as expensive equipment and difficulty in manufacturing compact devices. Recently, research has been actively underway on absorbance-based methods for applications in various devices, such as wearable devices.

[0004] Antioxidant measurement methods based on absorbance typically include two approaches. The first approach uses white light as the light source and a photodiode (PD) as a detector to receive light with specific wavelengths, such as 480 nm or 610 nm, by passing the light through a bandpass filter (BPF). However, this method is significantly affected by changes in hemoglobin signal due to stress. The second approach uses multi-wavelength light-emitting diodes (LEDs) (e.g., red, green, blue, and white wavelengths) and a photodiode. However, this method suffers from complex manufacturing processes and high production costs. Summary of the Invention

[0005] According to one aspect of an example embodiment, an apparatus for analyzing a substance of an object is provided, the apparatus comprising: a sensor unit including an image sensor and a plurality of light sources disposed around the image sensor; and a processor configured to drive the plurality of light sources to obtain the absorbance of each pixel based on the intensity of light received by each pixel of the image sensor, configured to correct the absorbance of each pixel based on the distance between the plurality of light sources and each pixel, and configured to analyze the substance of the object based on the corrected absorbance of each pixel.

[0006] Image sensors can include complementary metal-oxide-semiconductor (CMOS) image sensors.

[0007] The multiple light sources can be evenly arranged around the image sensor.

[0008] The first part of the plurality of light sources can be disposed on the first side of the image sensor, and the second part of the plurality of light sources can be disposed on the second side, with the second side facing the first side.

[0009] The plurality of light sources may include light sources configured to emit light of different wavelengths.

[0010] Image sensors may include color filters configured to adjust the measurement wavelength band.

[0011] The light sources among the plurality of light sources configured to emit light of the same wavelength can be arranged to face each other.

[0012] The plurality of light sources can be configured to emit light of a single wavelength, and the image sensor may include a color filter configured to adjust the measurement wavelength band.

[0013] The plurality of light sources can be configured to emit light of a single wavelength, and the image sensor may include a color filter for adjusting the measurement wavelength band.

[0014] The processor can also be configured to drive each of the plurality of light sources sequentially in a predetermined direction or in units of predetermined wavelengths.

[0015] The processor can also be configured to select one of the plurality of light sources based on at least one of measurement position or measurement depth, and to drive the selected light sources sequentially along a predetermined direction or in units of predetermined wavelength.

[0016] The processor can also be configured to combine the corrected absorbance for each pixel of each of the plurality of light sources and to analyze the material of the object based on the result of the combination.

[0017] The processor can also be configured to analyze the material at each pixel location of an object based on the absorbance of each pixel of the image sensor.

[0018] The processor can also be configured to correct the absorbance of each pixel by using a squared or logarithmic function of the distance between the plurality of light sources and each pixel of the image sensor.

[0019] The processor can also be configured to exclude light sources that do not meet predetermined criteria based on the absorbance of each pixel for each of the plurality of light sources, and to analyze the material of the object based on the absorbance of each pixel for the remaining light sources after excluding the light sources.

[0020] The substance of the object may include at least one of carotenoids, triglycerides, blood sugar, calories, cholesterol, protein, uric acid, water, or chromophores.

[0021] According to one aspect of an example embodiment, an apparatus for analyzing the substance of an object is provided, the apparatus comprising: a sensor unit including an image sensor, a plurality of first light sources disposed around the image sensor, and a second light source for fingerprint recognition; and a processor configured to drive the second light source to perform user authentication based on a fingerprint image of a finger obtained by the image sensor, and based on successful user authentication, to drive the plurality of first light sources to obtain the absorbance of each pixel based on the intensity of light received by each pixel of the image sensor, to correct the absorbance of each pixel based on the distance between the plurality of first light sources and each pixel, and to analyze the substance of the object based on the corrected absorbance of each pixel.

[0022] The device may further include a storage device configured to store light source driving conditions corresponding to each user, and the processor may further be configured to drive the plurality of first light sources based on successful user authentication and the light source driving conditions corresponding to the authenticated user.

[0023] The device may also include a storage device configured to store the material analysis history of each user, and the processor may also be configured to update the material analysis history of certified users based on the completion of material analysis for each object.

[0024] The processor can also be configured to provide information related to the finger's contact position based on the fingerprint image.

[0025] The processor can also be configured to detect the location of feature points of a finger based on a fingerprint image, and can provide the information based on the distance between the detected feature points and the center of the image sensor.

[0026] The processor can also be configured to detect the location of feature points of the finger based on the fingerprint image, determine the pixel of interest among the pixels of the image sensor, and obtain the absorbance based on the light intensity at the determined pixel of interest.

[0027] The processor can also be configured to detect the location of feature points of a finger based on a fingerprint image, and determine the light source to be driven among the plurality of first light sources based on the location of the detected feature points.

[0028] According to one aspect of an example embodiment, a method for analyzing the material of an object is provided, the method comprising: emitting light onto the object by driving a plurality of light sources disposed around an image sensor; receiving light scattered or reflected from the object by the image sensor; obtaining the absorbance of each pixel based on the intensity of light received by each pixel of the image sensor; correcting the absorbance of each pixel based on the distance between the plurality of light sources and each pixel; and analyzing the material of the object based on the corrected absorbance of each pixel.

[0029] The emission process may include sequentially driving each of the plurality of light sources in a predetermined direction or in units of a predetermined wavelength.

[0030] The emission step may include: selecting a light source from the plurality of light sources based on at least one of a measured position or a measured depth, and sequentially driving the selected light source along the predetermined direction or in units of the predetermined wavelength.

[0031] The analysis steps may include: combining the corrected absorbance for each pixel of each of the plurality of light sources, and analyzing the material of the object based on the result of the combination.

[0032] The analysis steps may include: analyzing the material at each pixel location of the object based on the absorbance of each pixel.

[0033] The correction steps may include correcting the absorbance of each pixel for the plurality of light sources by using a square or logarithmic function of the distance between the plurality of light sources and each pixel of the image sensor. Attached Figure Description

[0034] The above and other aspects, features and advantages of certain disclosed embodiments will become more apparent from the following description taken in conjunction with the accompanying drawings.

[0035] Figure 1 This is a block diagram illustrating an apparatus for analyzing substances according to a disclosed embodiment.

[0036] Figures 2A to 2D This is an illustration showing an example of the structure of a sensor section in a device for analyzing substances according to a disclosed embodiment.

[0037] Figure 3A and Figure 3B This is a diagram illustrating an example of a light source driving a sensor section in a device for analyzing substances according to a disclosed embodiment.

[0038] Figure 3C This is a diagram illustrating an example of the general relationship between carotenoid concentration and absorbance.

[0039] Figure 4 This is a block diagram illustrating an apparatus for analyzing substances according to another disclosed embodiment.

[0040] Figure 5 This is a block diagram illustrating an apparatus for analyzing substances according to yet another disclosed embodiment.

[0041] Figure 6 It means Figure 5 An example diagram illustrating the structure of the sensor section.

[0042] Figure 7A and Figure 7B This is a diagram illustrating an example of fingerprint image-guided contact location according to a disclosed embodiment.

[0043] Figure 8 This is a flowchart illustrating a method for analyzing a substance according to a disclosed embodiment.

[0044] Figure 9 This is a diagram illustrating a wearable device according to a disclosed embodiment.

[0045] Figure 10 This is a diagram illustrating a smart device according to a disclosed embodiment. Detailed Implementation

[0046] Details of the exemplary embodiments are included in the following detailed description and accompanying drawings. The advantages and features of the disclosure, as well as methods of implementing them, will become clearer from the following embodiments described in detail with reference to the accompanying drawings. Throughout the drawings and detailed description, unless otherwise described, the same reference numerals will be understood to refer to the same elements, features, and structures.

[0047] It will be understood that although the terms first, second, etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. Furthermore, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. It will also be understood that, unless explicitly described as the opposite, when an element is referred to as “including (contains)” another element, that element is not intended to exclude one or more other elements, but rather to include one or more other elements. In the following description, terms such as “unit” and “module” refer to units for performing at least one function or operation, and they can be implemented using hardware, software, or a combination thereof.

[0048] In the following, exemplary embodiments of an apparatus and method for analyzing a substance will be described in detail with reference to the accompanying drawings.

[0049] Figure 1This is a block diagram illustrating an apparatus 100 for analyzing substances according to a disclosed embodiment. Figures 2A to 2D This is a diagram showing an example of the structure of the sensor section in device 100. Figure 3A and Figure 3B This is a diagram showing an example of a light source in the sensor section of the drive device 100. Figure 3C This is a diagram illustrating an example of the general relationship between carotenoid concentration and absorbance.

[0050] Reference Figure 1 The device 100 for analyzing substances includes a sensor unit 110 and a processor 120.

[0051] The sensor unit 110 may include multiple light sources 111 and an image sensor 112. The multiple light sources may include light-emitting diodes (LEDs), laser diodes (LDs), phosphors, etc. All of the multiple light sources 111 may emit light of the same single wavelength or light of different wavelengths. In this case, different wavelengths may include infrared wavelengths, red wavelengths, green wavelengths, blue wavelengths, white wavelengths, etc. Alternatively, the multiple light sources 111 may emit light of two different wavelengths; in this case, the number of light sources 111 may be determined as a multiple of the minimum required number of wavelengths. For example, to emit three different wavelengths of light, at least two light sources may be provided for each wavelength.

[0052] Image sensor 112 may be a complementary metal-oxide-semiconductor (CMOS) image sensor. However, image sensor 112 is not limited to this and may also be a charge-coupled device (CCD) image sensor. Furthermore, instead of image sensor 112, for example, an array of photodiodes may be formed. In the example embodiment, by using, for example, LEDs and a CMOS image sensor with high spatial resolution, a multi-wavelength sensor section with multiple optical paths can be provided in a compact size.

[0053] Depending on the shape of the shape factor, the sensor unit 110 can have various shapes such as a fan shape, a circular shape, an elliptical shape, a polygonal shape, etc. For example, the sensor unit 110 can be formed into a circular shape, an elliptical shape, a square shape, etc., with the image sensor 112 disposed at the center of the sensor unit 110, and a plurality of light sources 111 uniformly disposed around the periphery of the image sensor 112. In another example, the sensor unit 110 can be formed into a circular shape, an elliptical shape, a square shape, etc., with the image sensor 112 disposed at the center of the sensor unit 110, and a plurality of light sources 111 disposed on a first side of the image sensor 112 and a second side of the image sensor 112 facing the first side. However, the shape of the sensor unit 110 and the arrangement of the image sensor 112 and the plurality of light sources 111 are not limited to the above examples.

[0054] Reference Figure 2A The sensor section 110 is circular in shape, with a CMOS image sensor (CIS) disposed at the center of the sensor section 110, and six LEDs evenly arranged around the periphery of the CIS. The six LEDs, including three pairs, can emit light of three different wavelengths λ1, λ2, and λ3, and can be arranged to face each other diagonally relative to the CIS. However, the number of LEDs, the number of wavelengths, and the number of LEDs for each wavelength are not particularly limited thereto.

[0055] Reference Figure 2B The sensor section 110 is rectangular in shape, with a CMOS image sensor (CIS) positioned at the center of the sensor section 110, and six LEDs positioned on either side of the CIS. In this case, as... Figure 2B As shown, LEDs can be positioned on both sides of the CIS to emit three different wavelengths λ1, λ2, and λ3.

[0056] Reference Figure 2C Multiple LEDs (e.g., W LEDs) in the sensor unit 110 can all emit light of the same single wavelength (e.g., white wavelength). In this case, the CIS, including a color filter 21 for adjusting the measurement wavelength band, can obtain information for each wavelength. (See reference...) Figure 2D Some of the multiple LEDs in the sensor unit 110 can emit light of different wavelengths, and the sensor unit 110 may include a color filter 22 for adjusting the measurement wavelength band in the CIS. Figure 2D As shown, while increasing the signal strength of a specific wavelength by using multi-wavelength LEDs, the measurement wavelength band can be precisely adjusted by using the color filter 22 of the CIS.

[0057] Return to reference Figure 1 The processor 120 can be electrically connected to the sensor unit 110. In response to a request to analyze the substance of an object, the processor 120 can drive multiple light sources 111 of the sensor unit 110 and can analyze the substance of the object based on data measured by the image sensor 112. In this case, the substance of the object may include carotenoids, triglycerides, blood glucose, calories, cholesterol, proteins, uric acid, water, chromophores, etc.

[0058] For example, processor 120 can sequentially drive all of a plurality of light sources in a time-division manner along a predefined direction (such as clockwise, counterclockwise, or zigzag). Alternatively, processor 120 can drive the light sources in a short-wavelength to long-wavelength order, or vice versa. For example, see reference Figure 2AThe processor 120 can first simultaneously turn on the LED with a first wavelength λ1 and turn off the remaining LEDs of other wavelengths. After a predetermined period of time, the processor 120 can simultaneously turn on the LED with a second wavelength λ2 and turn off the remaining LEDs of other wavelengths. After a predetermined period of time, the processor 120 can simultaneously turn on the LED with a third wavelength λ3 and turn off the remaining LEDs of other wavelengths. In this case, the driving conditions of the light source can be predefined (e.g., the driving sequence and current intensity of the light source, pulse duration, etc.).

[0059] In another example, the processor 120 may select some of a plurality of light sources 111 based on the measurement position, measurement depth, etc., and may sequentially drive the selected light sources 111 along a predetermined direction or in a predetermined order of wavelengths.

[0060] Reference Figure 3A To analyze material in the outer region or at a shallow depth within an object in contact with the sensor unit 110, CIS data can be obtained in six outer regions by combining three neighboring light sources with wavelengths λ1, λ2, and λ3. The material in the outer region or at a shallow depth can then be analyzed using these six combinations of CIS data. In this case, the CIS data can represent the intensity of light received by each pixel of the CIS. (Refer to...) Figure 3B To analyze material in the central region of an object in contact with the sensor unit 110 or at a deep depth within the object, CIS data can be obtained by combining three light sources of different wavelengths positioned at their longest distance from each other. Furthermore, the material in the central region or at a deep depth can be analyzed using two combinations of the obtained CIS data. However, these are merely examples, and various other combinations are possible. In this way, signals in various optical paths can be obtained even with a small sensor unit, and can be used to analyze material at various depths.

[0061] By driving multiple light sources 111, the processor 120 can analyze the material of an object based on pixel data received by the image sensor 112 (i.e., based on the intensity of light received by each pixel of the image sensor 112). For example, the processor 120 can calculate the absorbance of each pixel based on the light received by the image sensor 112 by using the light intensity of each pixel, and can analyze the material based on the absorbance of each pixel. Figure 3C The relationship between absorbance and carotenoid concentration is shown, demonstrating a constant correlation between absorbance and carotenoid concentration within a predetermined wavelength band. Absorbance can be obtained using Equation 1 below. Equation 1 is the equation used to calculate absorbance based on the Lambert-Beer law.

[0062] [Equation 1]

[0063]

[0064] Here, A represents absorbance, I0 represents the measured intensity of incident light measured using a standard reflector, and I represents the intensity of light reflected from the object, i.e., the intensity of light received by each pixel of the image sensor 112. Further, ε represents a predetermined absorption coefficient, b represents the optical path length, and c represents the substance concentration.

[0065] After obtaining the absorbance of each pixel for a specific light source 111, the processor 120 can correct the absorbance of each pixel to minimize the influence of the distance between the light source 111 and each pixel. For example, the processor 120 can correct the absorbance of each pixel based on the distance between the light source 111 and each pixel of the image sensor 112. Equation 2 below is an example of correcting the absorbance of each pixel.

[0066] [Equation 2]

[0067] A′=A / f(d)

[0068] Here, A represents the absorbance of each pixel, and A' represents the corrected absorbance of each pixel. Furthermore, d represents the distance between the driving light source and each pixel of the image sensor 112; and f(d) represents a predefined function for the distance (d) (e.g., a function of the square of the distance or a logarithmic function), but is not limited to this.

[0069] After correcting the absorbance of each pixel for each of the multiple light sources 111, the processor 120 can analyze the material of the object by appropriately combining the absorbance values ​​of each pixel for each light source 111.

[0070] For example, by using the absorbance of each pixel for the first light source and the absorbance of each pixel for the second light source, the processor 120 can combine the absorbance values ​​of corresponding pixels based on statistical values ​​(such as average, median, etc.) or using a predefined function, and can use Equation 1 above to estimate the carotenoid concentration of the object at each location corresponding to each pixel based on the combined absorbance values ​​of each pixel. In this case, the first light source and the second light source do not mean two light sources, but are only used to distinguish each of the driven light sources from each other.

[0071] In another example, processor 120 can estimate the concentration of a first carotenoid at each location of the object based on the absorbance of each pixel against a first light source, and can estimate the concentration of a second carotenoid at each location of the object based on the absorbance of each pixel against a second light source. In this case, if the wavelength of the first light source is different from the wavelength of the second light source, processor 120 can analyze carotenoid substances at different measurement depths and locations of the object.

[0072] Alternatively, the processor 120 can calculate an absorbance value for each light source by, for example, averaging the absorbance values ​​of each pixel for each light source, and based on the calculated absorbance value, the processor 120 can analyze the carotenoid concentration for each pixel in all areas in contact with the sensor unit 110. Alternatively, as described above, the processor 120 can estimate the carotenoid concentration in the areas in contact with the sensor unit 110 by combining all absorbance values ​​for each pixel of all driven light sources. However, the processor 120 is not limited to these examples, and can analyze substances using various methods based on measurement depth, measurement position, measurement purpose, etc.

[0073] Furthermore, the processor 120 can exclude light sources that do not meet predetermined criteria based on the light intensity or absorbance of each pixel for each light source, and can analyze the substance based on the absorbance of each pixel for the remaining light sources. For example, the processor 120 can obtain statistical values ​​(such as average, median, etc.) of the light intensity or absorbance of each pixel for each light source, and can exclude light sources with obtained statistical values ​​outside a predetermined range. Alternatively, the processor 120 can exclude light sources with the highest or lowest statistical value of absorbance obtained for each pixel for each light source. However, these are merely examples.

[0074] Figure 4 This is a block diagram illustrating an apparatus 400 for analyzing substances according to another disclosed embodiment.

[0075] Reference Figure 4 The apparatus 400 for analyzing substances includes a sensor unit 110, a processor 120, an output interface 410, a storage device 420, and a communication interface 430. The sensor unit 110 includes a light source 111 and an image sensor 112. The sensor unit 110 and the processor 120 have been described in detail above.

[0076] Output interface 410 can provide the user with the processing results of processor 120. For example, output interface 410 can display the processing results of processor 120 on a display screen. Output interface 410 can divide the display area into two or more areas, and can output information related to absorbance used for substance analysis in the first area, and output the substance analysis results in the second area. In addition, output interface 410 can output data showing the history of substance analysis over a predetermined time period in the form of a graph in the first area; and when the user selects an analysis result at any point in time on the graph, output interface 410 can output the substance analysis result at the selected time in the second area. In this case, if the estimated substance value falls outside the normal range, output interface 410 can provide a warning message by changing the color, line thickness, etc., or display the abnormal value together with the normal range, so that the user can easily identify the abnormal value of the estimated substance value. In addition, either together with visual output or separately, output interface 410 can output substance analysis results using non-visual methods such as voice, vibration, and touch through a voice output module (such as a speaker) or a tactile module.

[0077] The storage device 420 can store reference information to be used for material analysis, and results processed by the sensor unit 110 and / or processor 120 (e.g., data showing the intensity of light received at each pixel from each light source, the absorbance of each pixel, the corrected absorbance of each pixel, material analysis results, etc.). The reference information may include user characteristic information such as the user's age, gender, and health status. Additionally, the reference information may include light source driving conditions, material analysis models, etc.

[0078] Storage device 420 may include, but is not limited to, at least one of the following storage media: flash memory, hard disk memory, multimedia card micro memory, card memory (e.g., SD memory, XD memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disk and optical disk.

[0079] The communication interface 430 can communicate with external devices to send and receive various data related to material analysis from the external devices. In this case, the external device may include an information processing device such as a smartphone, tablet PC, desktop computer, or laptop computer. For example, the communication interface 430 can send material analysis results to a user's smartphone, allowing the user to manage and monitor the material analysis results (e.g., by using a device with relatively high performance). However, the communication interface 430 is not limited to this.

[0080] The communication interface 430 can communicate with external devices using various wired or wireless communication technologies, such as Bluetooth, Bluetooth Low Energy (BLE), Near Field Communication (NFC), WLAN, Zigbee, Infrared Data Association (IrDA), Wi-Fi Direct (WFD), Ultra Wideband (UWB), Ant+, Wi-Fi, Radio Frequency Identification (RFID), 3G, 4G, and 5G. However, this is merely an example and is not intended to be limiting.

[0081] Figure 5 This is a block diagram illustrating an apparatus 500 for analyzing substances according to yet another disclosed embodiment. Figure 6 It is shown Figure 5 An example diagram illustrating the structure of the sensor section. Figure 7A and Figure 7B This is a diagram illustrating an example of guiding contact location based on a fingerprint image.

[0082] Reference Figure 5 The device 500 for analyzing substances includes a sensor unit 110, a processor 120, an output interface 510, a storage device 520, and a communication interface 530. (The details regarding the connection to the sensor are omitted.) Figure 1 and Figure 4 The following description focuses on the different components of the same elements in the apparatuses 100 and 400 for analyzing substances shown in the figure.

[0083] The sensor unit 110 may include a first light source 111, an image sensor 112, and a second light source 113. The first light source 111 may be formed as a plurality of LEDs, etc., as described above, and may be arranged around the periphery of the image sensor 112. The image sensor 112 may include a CMOS image sensor. The second light source 113 may be a light source for user fingerprint authentication. The second light source 113 may include one or more LEDs, LDs, etc.

[0084] Reference Figure 6The image sensor 112 can be disposed at the center of the sensor section 110, and a plurality of LEDs 111 can be evenly arranged around the periphery of the image sensor 112. Furthermore, as a second light source 113, one LED can be disposed on one side of the image sensor 112, or two LEDs FL1 and FL2 can be disposed on both sides of the image sensor 112. However, the number and arrangement of the second light source 113 are not limited thereto. (Refer to the above...) Figures 2A to 2D Examples of various shapes of the sensor unit 110 and various arrangements of the first light source 111 are described in detail, so that their detailed description will be omitted.

[0085] Once the user places their finger on the sensor unit 110, the processor 120 can drive the second light source 113 so that the image sensor 112 can acquire a fingerprint image and compare the fingerprint image acquired by the image sensor 112 with reference fingerprint image data stored in the storage device 520 to perform user authentication.

[0086] For example, if the device 500 for analyzing substances is installed in a wearable device or mobile device such as a smartphone for a specific user, the processor 120 can prevent others from viewing the user's substance analysis data or performing substance analysis functions through the device 500. Alternatively, the device 500 for analyzing substances can be installed in a device that can be shared by multiple users (e.g., a large home appliance such as a refrigerator, TV, etc., or a device in a medical facility). In this case, each of the multiple users can register a fingerprint image of the finger to be used for user authentication in order to use the device. Therefore, the use of the device 500 for analyzing substances can be controlled by authentication of the user's fingerprint.

[0087] Storage device 520 can manage data for each user with permissions to use device 500 for analyzing substances. For example, storage device 520 can store reference fingerprint image data that can be used for substance analysis, access permissions for each function, characteristic information such as the user's age, gender, health status, and light source driving conditions for each user.

[0088] Based on successful user authentication, processor 120 can drive the first light source 111 according to the light source driving conditions set for authorized users. Furthermore, once the material analysis results for an authorized user are obtained, processor 120 can update the user's material analysis history stored in storage device 520.

[0089] In addition, based on the user's successful authentication, the processor 120 can guide the finger's contact position based on the fingerprint image obtained from the user. Figure 7AAn example of a fingerprint image of a finger is shown. Once the fingerprint image is acquired, the processor 120 can detect feature points (e.g., the fingerprint center FC and / or fingerprint orientation) from the fingerprint image. Additionally, the processor 120 can determine the contact position based on the fingerprint center FC. For example, if the distance between the fingerprint center FC and the center IC of the image sensor 112 is greater than a predetermined threshold, the processor 120 can determine that the finger contact position is inappropriate.

[0090] The output interface 510 can output guidance information regarding the finger's contact position under the control of the processor 120. For example, the output interface 510 can display a fingerprint image on a display and can display one or more markers representing the fingerprint center FC and / or center IC of the image sensor 112, which are superimposed on the fingerprint image. Additionally, if the distance between the fingerprint center FC and the center IC of the image sensor 112 is greater than a predetermined threshold, the output interface 510 can display markers (e.g., arrows) to guide the finger's fingerprint center FC toward the center IC of the image sensor 112.

[0091] Furthermore, as described above, the processor 120 can determine pixels in the region of interest among the pixels of the image sensor 112 based on the fingerprint image, and can obtain the absorbance by using the light intensity of the pixels in the determined region of interest. For example, Figure 7B This is an illustration showing an example of the light intensity of a pixel received by image sensor 112. Processor 120 can determine a predetermined region as a region of interest (ROI) R based on the fingerprint center FC and the contact direction of the finger in the fingerprint image. The size of the RROI can be predefined. The fingerprint center FC can be determined as the center of the RROI, but is not limited thereto. The shape of the RROI can be along... Figure 7B The rectangular shape shown is for the contact direction, but the shape is not limited to this and can be various shapes such as circular shapes, elliptical shapes, etc.

[0092] Additionally, the processor 120 can determine the finger's contact position based on the fingerprint image, and can determine the light source to be driven from among a plurality of light sources 111 based on the determined finger's contact position. For example, if the fingerprint center FC of the finger is offset from the center IC of the image sensor 112 in a specific direction (e.g., to the right), the processor 120 can drive the light source 111 located on the right side.

[0093] The communication interface 530 can receive reference fingerprint image data from an external device (such as a user's smartphone) and can store the data in the storage device 520. Alternatively, the communication interface 530 can send the processing results of the processor 120 to the external device.

[0094] Figure 8This is a flowchart illustrating a method for analyzing a substance according to a disclosed embodiment.

[0095] Figure 8 The method can be derived from Figure 1 and Figure 4 The analysis is performed by either of the devices 100 and 400 for analyzing substances. Devices 100 and 400 have been described in detail above, so they will be briefly described below.

[0096] In 810, the apparatuses 100 and 400 for analyzing substances can drive light sources to emit light onto an object. Multiple light sources can be provided, each emitting light of different wavelengths. The apparatuses 100 and 400 for analyzing substances can combine two or more light sources by taking into account the measurement location and / or measurement depth of the object, and can drive the combined light sources. The apparatuses 100 and 400 for analyzing substances can drive multiple light sources in a time-division manner.

[0097] Then, in 820, the devices 100 and 400 for analyzing the substance can receive light scattered or reflected from the object via an image sensor for each driven light source. In this case, the image sensor can be positioned at the center of the sensor section, and multiple light sources can be arranged around the periphery of the image sensor.

[0098] Subsequently, in 830, the devices 100 and 400 for analyzing the substance can obtain the absorbance of each pixel for each driven light source based on the light intensity of each pixel received by the image sensor.

[0099] Next, in 840, the devices 100 and 400 for analyzing the substance can correct the absorbance of each pixel of the image sensor based on the distance between the driving light source and each pixel. For example, the devices 100 and 400 for analyzing the substance can obtain the distance between the driving light source and each pixel, and can obtain the corrected absorbance of the pixel by dividing the absorbance value of the pixel by the square of the distance. However, the correction equation is not limited to this and can be defined in various ways, such as a logarithmic function.

[0100] Then, at 850, once absorbance data for each pixel of the driven light source is obtained, the devices 100 and 400 for analyzing the substance can analyze the substance of the object using the obtained absorbance data. As described above, based on the combination of absorbance data for each light source, the devices 100 and 400 for analyzing the substance can analyze the substance at each position and depth of the object and at each wavelength.

[0101] Figure 9This is a diagram illustrating a wearable device according to a disclosed embodiment. Figure 9 The wearable device may be a smartwatch or smart band worn on the wrist, and may include one or more of the various embodiments of the devices 100, 400 and 500 described above for analyzing substances.

[0102] Reference Figure 9 The wearable device 900 includes a main body 910 and a strap 930. Various modules of the devices 100, 400 and / or 500 for analyzing substances can be installed in the main body 910.

[0103] The main body 910 can be worn on a user's wrist using a strap 930. The main body 910 may include various modules for various functions of the wearable device 900. A battery may be embedded in the main body 910 or the strap 930 to supply power to the various modules of the wearable device 900. The strap 930 may be connected to the main body 910. The strap 930 may be flexible to bend around the user's wrist. The strap 930 may include a first strap and a second strap that are separate from each other. One end of the first strap and the second strap is connected to the main body 910, and their other ends may be connected to each other via a connecting means. In this case, the connecting means may include, but are not limited to, magnetic connections, Velcro connections, pin connections, etc. Furthermore, the strap 930 is not limited to these and may be integrally formed as a non-removable strap.

[0104] Furthermore, the sensor unit 920 can be mounted within the main body 910. The sensor unit 920 may include a CMOS image sensor disposed at its center and multiple light sources arranged around the periphery of the image sensor. The sensor unit 920 may have a shape that can vary depending on its shape factor. Figure 9 The shape shown is a rectangle or various other shapes (such as a circle, an ellipse, etc.). In this case, the sensor unit 920 may include a separate light source for fingerprint authentication.

[0105] The processor can be installed in the main body 910 and can be electrically connected to the module of the wearable device 900. The processor can obtain the absorbance based on the light intensity of the pixels received by the image sensor of the sensor unit 920, and can obtain the concentration of antioxidants (e.g., carotenoids) based on the obtained absorbance. The processor can reduce the influence of distance by correcting the absorbance of each pixel based on the distance between the light source and each pixel of the image sensor. When a user's finger contacts the sensor unit 920, the processor can perform user authentication by driving the light source for fingerprint authentication.

[0106] In addition, the main body 910 may include a storage device for storing various reference information and information processed by various modules.

[0107] Additionally, the main body 910 may include a manipulator 940 that receives user control commands and transmits the received control commands to the processor. The manipulator 940 may have a power button for inputting commands to turn the wearable device 900 on / off.

[0108] Furthermore, a display for outputting information to the user can be mounted on the front surface of the main body 910. The display may include a touchscreen for receiving touch input. The display can receive touch input from the user and send the touch input to the processor, and can display the processor's processing results.

[0109] In addition, the main body 910 may include a communication interface for communicating with external devices. The communication interface can send the material analysis results to external devices (e.g., a user's smartphone).

[0110] Figure 10 This is a diagram illustrating a smart device according to an embodiment of the present disclosure. In this case, the smart device may include a smartphone, a tablet PC, etc. The smart device may include various embodiments of the above-described apparatus 100, 400, and 500 for analyzing substances.

[0111] Reference Figure 10 The smart device 1000 includes a main body 1010 and a sensor unit 1020 mounted on one surface of the main body 1010. For example, the sensor unit 1020 may include a CMOS image sensor 1022 disposed at its center and a plurality of light sources 1021 disposed around the periphery of the image sensor 1022. Furthermore, the sensor unit 1020 may also include a separate light source for fingerprint authentication. The structure of the sensor unit 1020 has been described in detail above, therefore its description will be omitted.

[0112] Furthermore, a display can be mounted on the front surface of the main body 1010. The display can visually output material analysis results, etc. The display may include a touch screen and can receive information input via the touch screen and send the information to the processor.

[0113] The processor can obtain the absorbance based on the light intensity of each pixel received by the image sensor when a finger contacts the sensor unit 1020, and can analyze the material of the object by correcting the absorbance. Additionally, when a finger contacts the sensor unit 1020, the processor can perform user authentication based on the fingerprint image of the finger. Detailed description of this will be omitted.

[0114] The disclosure can be implemented as computer-readable code written on a computer-readable recording medium. The computer-readable recording medium can be any type of recording device in which data is stored in a computer-readable manner.

[0115] Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage devices, and carrier waves (e.g., data transmission over the Internet). Computer-readable recording media can be distributed across multiple computer systems connected to a network, allowing computer-readable code to be written into and executed from them in a distributed manner. Programs, code, and code segments used to implement publicly disclosed functions can be readily derived by a programmer of ordinary skill in the art to which they pertain.

[0116] According to exemplary embodiments, at least one of the components, elements, modules, and units described herein can be implemented as various numbers of hardware, software, and / or firmware structures performing the functions described above. For example, at least one of these components, elements, and units can use a direct circuit structure (such as a memory, processor, logic circuit, lookup table, etc.) that can perform its respective function under the control of one or more microprocessors or other control devices. Additionally, at least one of these components, elements, and units can be embodied by a portion of a module, program, or code containing one or more executable instructions for performing specific logical functions, and executed by one or more microprocessors or other control devices. Furthermore, at least one of these components, elements, and units can also include, or be implemented by, a processor such as a central processing unit (CPU), microprocessor, etc., performing its respective function. Two or more of these components, elements, and units can be combined into a single component, element, or unit that performs all the operations or functions of the combined two or more components, elements, or units. Additionally, at least a portion of the function of at least one of these components, elements, and units can be performed by another of these components, elements, and units. Furthermore, although a bus is not shown in the block diagram, communication between components, elements, or units can be performed via a bus. The functional aspects of the above example embodiments can be implemented using algorithms executed on one or more processors. Moreover, the components, elements, or units represented by blocks or processing operations can employ any number of related techniques for electronic configuration, signal processing and / or control, data processing, etc.

[0117] Although some embodiments have been shown and described, those skilled in the art will understand that changes may be made to the embodiments without departing from the principles and spirit of the disclosure, the scope of which is limited in the claims and their equivalents.

Claims

1. An apparatus for analyzing a substance of an object, the apparatus comprising: The sensor unit includes an image sensor and multiple light sources disposed around the image sensor; as well as The processor is configured to drive the plurality of light sources to obtain the absorbance of each pixel based on the intensity of light received by each pixel of the image sensor from each of the plurality of light sources, to correct the absorbance of each pixel based on the distance between the plurality of light sources and each pixel of the image sensor, and to analyze the material of the area of ​​the object in contact with the sensor based on the corrected absorbance of each pixel.

2. The device according to claim 1, wherein, Image sensors include complementary metal-oxide-semiconductor image sensors.

3. The device according to claim 1, wherein, The multiple light sources are evenly arranged around the image sensor.

4. The device according to claim 1, wherein, The first portion of the plurality of light sources is disposed on the first side of the image sensor, and the second portion of the plurality of light sources is disposed on the second side, with the second side facing the first side.

5. The device according to any one of claims 1 to 4, wherein, The plurality of light sources includes light sources configured to emit light of different wavelengths.

6. The device according to claim 5, wherein, The image sensor includes a color filter configured to adjust the measurement wavelength band.

7. The device according to any one of claims 1 to 4, wherein, The multiple light sources configured to emit light of the same wavelength are arranged to face each other.

8. The device according to any one of claims 1 to 4, wherein, The plurality of light sources are configured to emit light of a single wavelength, and the image sensor includes a color filter configured to adjust the measurement wavelength band.

9. The device according to any one of claims 1 to 4, wherein, The processor is also configured to drive each of the plurality of light sources sequentially in a predetermined direction or in units of predetermined wavelengths.

10. The device according to any one of claims 1 to 4, wherein, The processor is also configured to select one of the plurality of light sources based on at least one of measurement position and measurement depth, and to drive the selected light sources sequentially along a predetermined direction or in units of predetermined wavelength.

11. The device according to any one of claims 1 to 4, wherein, The processor is also configured to combine the corrected absorbance of each pixel for the plurality of light sources and to analyze the material of the object based on the result of the combination.

12. The device according to any one of claims 1 to 4, wherein, The processor is also configured to analyze the material at each pixel location of the object based on the absorbance of each pixel of the image sensor.

13. The device according to any one of claims 1 to 4, wherein, The processor is also configured to correct the absorbance of each pixel by using a squared or logarithmic function of the distance between the plurality of light sources and each pixel of the image sensor.

14. The device according to any one of claims 1 to 4, wherein, The processor is also configured to exclude light sources that do not meet a predetermined standard based on the absorbance of each pixel for each of the plurality of light sources, and to analyze the material of the object based on the absorbance of each pixel for the remaining light sources after excluding the light sources that do not meet the predetermined standard.

15. The device according to any one of claims 1 to 4, wherein, The substances in question include at least one of carotenoids, triglycerides, blood sugar, calories, cholesterol, protein, uric acid, water, and chromophores.

16. An apparatus for analyzing a substance of an object, the apparatus comprising: The sensor unit includes an image sensor, a plurality of first light sources disposed around the image sensor, and a second light source for fingerprint recognition; as well as The processor is configured to drive a second light source to perform user authentication based on a fingerprint image of a finger obtained by an image sensor, and based on successful user authentication, to drive the plurality of first light sources to obtain the absorbance of each pixel based on the intensity of light received by each pixel of the image sensor from each of the plurality of first light sources, to correct the absorbance of each pixel based on the distance between the plurality of first light sources and each pixel of the image sensor, and to analyze the material of the area of ​​the object in contact with the sensor based on the corrected absorbance of each pixel.

17. The device of claim 16, further comprising a storage device configured to store light source driving conditions corresponding to each user. in, The processor is also configured to drive the plurality of first light sources based on successful user authentication and the light source driving conditions corresponding to the authenticated user.

18. The apparatus of claim 16, further comprising a storage device configured to store the material analysis history of each user. in, The processor is also configured to update the certified user’s material analysis history based on the completion of the material analysis of the object.

19. The device according to any one of claims 16 to 18, wherein, The processor is also configured to provide information related to the finger's contact position based on the fingerprint image.

20. The device according to claim 19, wherein, The processor is also configured to detect the location of feature points of the finger based on the fingerprint image, and to provide the information based on the distance between the detected feature points and the center of the image sensor.

21. The device according to any one of claims 16 to 18, wherein, The processor can also be configured to detect the location of feature points of the finger based on the fingerprint image, determine the pixel of interest among the pixels of the image sensor, and obtain the absorbance based on the light intensity at the determined pixel of interest.

22. The device according to any one of claims 16 to 18, wherein, The processor is also configured to detect the location of feature points of the finger based on the fingerprint image, and to determine the light source to be driven among the plurality of first light sources based on the location of the detected feature points.

23. A method for analyzing the substance of an object, the method comprising: Light is emitted onto the object by driving multiple light sources positioned around the image sensor; The image sensor receives light scattered or reflected from the object from each of the plurality of light sources; The absorbance of each pixel is obtained based on the intensity of light received by each pixel of the image sensor; The absorbance of each pixel is corrected based on the distance between the multiple light sources and each pixel of the image sensor; as well as The material of the object in contact with the sensor unit, which includes the image sensor and the multiple light sources, is analyzed based on the corrected absorbance of each pixel.

24. The method according to claim 23, wherein, The emission process includes sequentially driving each of the plurality of light sources in a predetermined direction or in units of a predetermined wavelength.

25. The method according to claim 24, wherein, The emission steps include: selecting a light source from the plurality of light sources based on at least one of the measurement position and measurement depth, and sequentially driving the selected light source along a predetermined direction or in units of a predetermined wavelength.

26. The method according to any one of claims 23 to 25, wherein, The analysis steps include: combining the corrected absorbance of each pixel for the multiple light sources, and analyzing the material of the object based on the combination result.

27. The method according to any one of claims 23 to 25, wherein, The analysis steps include: analyzing the material at each pixel location of the object based on the absorbance of each pixel.

28. The method according to any one of claims 23 to 25, wherein, The correction steps include: correcting the absorbance of each pixel for each of the plurality of light sources by using the square or logarithmic function of the distance between the plurality of light sources and each pixel of the image sensor.

Images