A finger ring glow image comparison method and system

Abstract

The present invention discloses a finger ring glow image comparison method and system, the method includes: for the ten finger glow images collected by the GDV device, the present invention proposes a finger ring glow image comparison method. It can be used for finger glow image retrieval, and for comparison with the average characteristics of a certain group of people. When a certain group of people have a certain disease that is displayed as a bulge or depression in a certain part of the finger ring, it can be inferred whether the current test person is likely to have this disease. It is also possible to calculate the average characteristics of two groups of people and analyze whether the two groups of people are separable. The accuracy of similarity calculation is improved by the method provided by the present invention.

Description

Technical Field

[0001] The present invention relates to the technical field of finger glow defect detection, and in particular to a finger annular glow image comparison method and system. Background Art

[0002] Traditional Chinese medicine is a treasure of our Chinese nation. It is the crystallization of wisdom that has been continuously improved by many generations over thousands of years. With the development of the times and the progress of society, as well as the popularization of the concept of preventing diseases by traditional Chinese medicine, the combination of traditional Chinese medicine and modern technology has produced a series of modern achievements. In addition to the modern extraction and production of traditional Chinese medicine, the diagnostic methods of traditional Chinese medicine are also developing in the direction of automation and digitization. In recent years, with the gradual development of image processing technology and the continuous maturity of artificial intelligence technologies such as machine learning and deep learning, these technologies have begun to be applied to medical diagnosis, and a variety of digital methods of traditional Chinese medicine have been produced.

[0003] In 1995, the team led by Professor Pr. Korotkov developed an innovative technology: Gas Discharge Visualization (GDV). The team combined traditional Chinese medicine, acupuncture, and quantum medicine such as Indian Ayurveda medicine, advocating the transformation from "treating existing diseases" to "preventing diseases". However, when comparing the images of the acquired finger glow, there is a defect of low accuracy in similarity calculation. Summary of the invention

[0004] Therefore, the finger annular glow image comparison method and system provided by the present invention overcomes the defect of low similarity calculation accuracy when performing finger glow image comparison in the prior art.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a finger ring glow image comparison method, comprising:

[0007] Preprocessing the finger image of the gas release imaging technology GDV of the first preset object, generating the inner contour and outer contour of each finger glow by polar coordinate transformation;

[0008] According to the pixel points of the inner contour, the ellipse shape is fitted using a first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle;

[0009] Locate the finger direction using a second preset function based on the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse, and the rotation angle;

[0010] Divide the ring into zones according to the direction of the fingers;

[0011] According to the entire finger glow image, the average thickness of the outer contour and the inner contour of the entire finger glow image is calculated using the ordinates of the outer contour and the inner contour after polar coordinate transformation;

[0012] Perform histogram statistics on each partition, and use the ordinates of the outer and inner contours after polar coordinate transformation to calculate the thickness value of the ring partition;

[0013] Determine the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the finger ring partition;

[0014] Repeat the above steps to determine the defect detection degree of the finger glow of the second preset object;

[0015] The similarity between the first preset object and the second preset object is calculated according to the defect detection degree of the first preset finger glow and the defect detection degree of the finger glow of the second preset object.

[0016] Optionally, the first preset function includes: a fitEllipse function in opencv.

[0017] Optionally, the ring is partitioned according to the finger directions, including:

[0018] According to the finger direction, 360 degrees is divided into a first preset number of portions of a first preset angle, wherein the first preset number of portions is the number of zones of the ring zone.

[0019] Optionally, the average thickness of the outer contour and inner contour of the entire finger glow image is calculated by the following formula:

[0020]

[0021] in, represents the ordinate of the outer contour of the i-th point, It represents the ordinate of the inner contour of the i-th point, and N represents the number of points.

[0022] Optionally, determining the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the ring partition includes:

[0023] When the thickness value of the ring partition is larger than the mean value, the finger glow bulge is more serious;

[0024] When the thickness value of the ring partition is smaller than the mean value, the finger glow depression is more serious.

[0025] Optionally, partitioning the ring includes: partitioning each finger.

[0026] Optionally, the similarity between the first preset object and the second preset object is calculated by the following formula:

[0027]

[0028] Wherein, ab represents the first preset object and the second preset object respectively, a single finger partition is set to N parts, and the histogram of the current partition is

[0029] In a second aspect, an embodiment of the present invention provides a finger ring glow image comparison system, comprising:

[0030] The inner and outer contour data acquisition module is used to pre-process the finger image of the gas release imaging technology GDV of the first preset object, and generate the inner and outer contours of each finger glow by using polar coordinate transformation;

[0031] An ellipse fitting module is used to fit the ellipse shape according to the pixel points of the inner contour by using a first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle;

[0032] A finger direction positioning module, used to locate the finger direction using a second preset function according to the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse and the rotation angle of the ellipse;

[0033] The ring partitioning module is used to partition the ring according to the finger direction;

[0034] The average thickness calculation module is used to calculate the average thickness of the outer contour and the inner contour of the entire finger glow image according to the entire finger glow image using the ordinates of the outer contour and the inner contour after polar coordinate transformation;

[0035] The histogram statistics module is used to perform histogram statistics on each partition and calculate the thickness value of the ring partition using the ordinates of the outer contour and inner contour after polar coordinate transformation;

[0036] A first preset defect detection module, used to determine the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the ring partition;

[0037] A second preset defect detection module, repeating the inner and outer contour data acquisition module to the first preset defect detection module, determines the defect detection degree of the finger glow of the second preset object;

[0038] The comparison module calculates the similarity between the first preset object and the second preset object according to the defect detection degree of the first preset finger glow and the defect detection degree of the finger glow of the second preset object.

[0039] In a third aspect, an embodiment of the present invention provides a terminal, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the finger ring glow image contrast method described in the first aspect of the embodiment of the present invention.

[0040] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the finger ring glow image comparison method described in the first aspect of the embodiment of the present invention.

[0041] The technical solution of the present invention has the following advantages:

[0042] The present invention provides a finger ring glow image comparison method and system. For the ten finger glow images collected by the GDV device, the embodiment of the present invention proposes a finger ring glow image comparison method. It can be used for finger glow image retrieval, that is, to find a person's finger glow image in the finger glow image library. It can also be used to compare with the average characteristics of a certain group of people. If a certain group of people have a certain disease that is displayed as a bulge or depression in a certain part of the finger ring, it can be inferred whether the current person being tested is likely to have this disease. It is also possible to calculate the average characteristics of two groups of people and analyze whether the two groups of people are separable. The accuracy of the calculation is improved by the method provided by the embodiment of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A flowchart of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0045] Figure 2 A specific example of a finger ring glow image comparison method provided by an embodiment of the present invention locates and segments a contour image of a single finger glow area;

[0046] Figure 3 A finger glow inner contour diagram of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0047] Figure 4A finger glow outer contour diagram of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of an ellipse obtained by fitting the inner contour of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0049] Figure 6 A schematic diagram of corresponding parameters of an ellipse according to a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0050] Figure 7 A schematic diagram of partitioning of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0051] Figure 8 A schematic diagram of partitioning of another specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0052] Fig. 9 An outer contour diagram of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0053] Fig.10 The inner contour of a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0054] Fig.11a , Fig.11b They are respectively the inner contour diagram of the first partition and its schematic diagram under polar coordinates when there are four partitions in step S4 of a specific example of a finger annular glow image comparison method provided by an embodiment of the present invention;

[0055] Fig.12a , Figure 12b They are respectively the outer contour image of the first partition and its schematic diagram under polar coordinates when there are four partitions in step S4 of a specific example of a finger annular glow image comparison method provided by an embodiment of the present invention;

[0056] Fig.13 A histogram of the left thumb divided into 7 parts, which is a specific example of a finger ring glow image comparison method provided by an embodiment of the present invention;

[0057] Fig.14 A module composition diagram of a finger ring glow image comparison system provided by an embodiment of the present invention;

[0058] Fig.15 A composition diagram of a specific example of a terminal provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0061] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can also be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0062] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0063] Example 1

[0064] The embodiment of the present invention provides a finger ring glow image comparison method, such as Figure 1 As shown, the following steps are included:

[0065] Step S1: pre-processing the finger image of the gas release imaging technology GDV of the first preset object, and generating the inner contour and outer contour of each finger glow by polar coordinate transformation.

[0066] In an embodiment of the present invention, preprocessing the finger image of the gas release imaging technology GDV of the first preset object includes: denoising the acquired ten finger images, such as Figure 2 As shown, the single finger glow area is located and segmented, such as Figure 3 , Figure 4 As shown, polar coordinate transformation is used to obtain the inner and outer contours of the finger glow.

[0067] Step S2: According to the pixel points of the inner contour, the ellipse shape is fitted using a first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle.

[0068] In the embodiment of the present invention, the first preset function includes: fitEllipse function in opencv. This is only an example and is not limited to this. In actual applications, a corresponding function is selected according to actual needs.

[0069] In the embodiment of the present invention, according to the pixel points on the inner contour, the function fitEllipse in opencv can be used to complete it, for example: RotatedRect fitEllipse (InputArraypoints), such as Figure 5 As shown in the figure, the ellipse is fitted by this function to the inner contour. At the same time, the circumscribed rectangle of the ellipse is obtained. Thus, the major axis, minor axis, center point of the ellipse and rotation angle of the ellipse are obtained.

[0070] Step S3: Locate the finger direction using a second preset function based on the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse and the rotation angle.

[0071] In the embodiment of the present invention, the second preset function is not limited here, and a corresponding function is selected according to actual needs in actual applications. The second preset function can be the same as the first preset function.

[0072] In a specific embodiment, in the function of step S2, the pixel points on the inner ellipse are taken as input points, and the returned circumscribed rectangle is set as rect, such as Figure 6 As shown, the corresponding parameters of the corresponding ellipse are: the major axis and minor axis of the corresponding ellipse are rect.size.width and rect.size.height respectively (the larger value is the major axis, AD is the major axis and EF is the minor axis), the center point of the ellipse is rect.center (point C here), and the rotation angle of the ellipse is rect.angle (angle BCA here).

[0073] The center point C and the center point A of the short side of the rectangle can form a straight line, that is, the long axis direction CA is obtained, such as Figure 6 The direction of the middle arrow is the direction of the finger. In the embodiment of the present invention, the preset direction of the finger is upward, that is, the angle BCA needs to be within 0 degrees to 180 degrees to be the correct finger direction, otherwise it is the opposite direction.

[0074] Step S4: partition the ring according to the finger directions.

[0075] In an embodiment of the present invention, partitioning the ring according to the finger direction includes: dividing 360 degrees into a first preset number of portions of a first preset angle according to the finger direction, wherein the first preset number of portions is the number of zones of the ring partition.

[0076] In the embodiment of the present invention, according to the finger direction, such as Figure 7 As shown, 360 degrees is divided into 4 equal parts. Figure 8 As shown, or divided equally into 8 parts. No limitation is made here, and it can be divided into any angle and any number of parts as needed.

[0077] Step S5: According to the entire finger glow image, the average thickness of the outer contour and the inner contour of the entire finger glow image is calculated using the ordinates of the outer contour and the inner contour after polar coordinate transformation.

[0078] In the embodiment of the present invention, the average thickness of the outer contour and the inner contour of the entire finger glow image is calculated by the following formula:

[0079]

[0080] in, represents the ordinate of the outer contour of the i-th point, It represents the ordinate of the inner contour of the i-th point, and N represents the number of points.

[0081] In a specific embodiment, for the entire finger glow image, the outer contour after polar coordinate transformation is subtracted from the ordinate of the inner contour, and then the average is calculated, such as Fig. 9 As shown, it corresponds to the outer contour. Fig.10 As shown, it corresponds to the inner contour.

[0082] In the embodiment of the present invention, it is the average thickness in polar coordinates, because in the end, this patent only needs to calculate the percentage of thickness deviation, so it is not necessary to calculate the thickness in Cartesian coordinates. For the defective part of the finger, because the inner and outer contours are both 0, the thickness finally calculated is also 0.

[0083] Step S6: Perform histogram statistics on each partition, and calculate the thickness value of the ring partition using the ordinates of the outer contour and inner contour after polar coordinate transformation.

[0084] In a specific embodiment, the inner and outer contours of the ring partitions are obtained: when the 4 partitions in the above step S4 are obtained, Figure 11a-Figure 11b , Figure 12a-12b As shown, the inner and outer contours of the first partition, and the corresponding polar coordinate images; it can be seen that this image does not start from the coordinate origin of the complete polar coordinate contour, so it is also possible to calculate the angle offset for each partition first, and then perform histogram statistics.

[0085] Partition histogram statistics: Perform histogram statistics on each partition. Similarly, subtract the ordinate of the inner contour from the outer contour after the polar coordinate transformation mentioned above to obtain the ring partition thickness value. For ease of observation, this patent divides the histogram into 3 parts, or 7 parts, and of course it can be divided into any number of parts. The larger the value than the mean, the more severe the bulge, and the smaller the value than the mean, the more severe the depression. Based on the histogram, the degree of defect of a partition of a certain finger can be found. The definitions of 3 parts and 7 parts are given below, and of course other ways of dividing can also be used.

[0086] In one specific embodiment, when divided into 3 portions:

[0087] bin[0]++if y<aveY*(1-T)and y∈Y j

[0088] bin[1]++if y≥aveY*(1-T)and y≤aveY*(1+T)and y∈Y j

[0089] bin[2]++if y>aveY*(1+T)and y∈Y j

[0090] Where bin[k], k∈[0,1,2] represents the number in the kth partition, aveY represents the mean thickness of the current partition, and Y j represents all thickness values ​​of the jth partition, T is a threshold that can control the number of thickness values ​​near the mean, and this patent takes 0.1.

[0091] Then we can calculate the proportion of each portion: It can be seen that hist[0] represents the concave ratio and hist[2] represents the convex ratio.

[0092] In another specific embodiment, divided into 7 portions:

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100] Among them, stdev represents the standard deviation of the glow thickness of the entire finger; other symbols are similar to those when divided into 3 parts; the proportion of each part can still be calculated:

[0101] hist[0], hist[1], hist[2] represent the proportion of depressions of different degrees;

[0102] hist[4], hist[5], hist[6] represent the proportion of protrusions of different degrees.

[0103] In the embodiment of the present invention, the histogram shows that for ten fingers, each partition of each finger has a histogram. In the embodiment of the present invention, Fig.13 As shown, only an example of the histogram of the left thumb divided into 7 parts is given.

[0104] Step S7: Determine the defect detection degree of the finger glow according to the average thickness and the thickness value of the ring partition.

[0105] In an embodiment of the present invention, the defect detection degree of the finger glow is determined according to the average thickness and the thickness value of the ring partition, including: when the thickness value of the ring partition is larger than the average value, the finger glow is more seriously convex; when the thickness value of the ring partition is smaller than the average value, the finger glow is more seriously concave.

[0106] Step S8: Repeat steps S1 to S7 to determine the defect detection degree of the finger glow of the second preset object.

[0107] Step S9: Calculate the similarity between the first preset object and the second preset object according to the defect detection degree of the first preset finger glow and the defect detection degree of the finger glow of the second preset object.

[0108] In the embodiment of the present invention, the similarity between the first preset object and the second preset object is calculated by the following formula:

[0109]

[0110] Wherein, a and b represent the first preset object and the second preset object respectively, a single finger partition is set to N parts, and the histogram of the current partition is:

[0111]

[0112] In a specific embodiment, in order to compare the similarity of the finger glow images of two persons a and b, the embodiment of the present invention uses the histogram distance as an evaluation index of the similarity.

[0113] First, a single finger partition is set to N parts, then the histogram of the current partition is:

[0114]

[0115] Here, N can be 3 or 7, without limitation, and can also be a larger number.

[0116] Secondly, calculate the similarity of the single fingers of a and b. The formula is as follows:

[0117]

[0118] Finally, the similarities of the 10 pairs of fingers are averaged to get the overall similarity:

[0119]

[0120] The finger ring glow image comparison method provided in the embodiment of the present invention, for the ten finger glow images collected by the GDV device, the embodiment of the present invention proposes a finger ring glow image comparison method. It can be used for finger glow image retrieval, that is, to find a person's finger glow image in the finger glow image library. It can also be used to compare with the average characteristics of a certain group of people. If a certain group of people have a certain disease that is displayed as a bulge or depression in a certain part of the finger ring, it can be inferred whether the current test person is likely to have this disease. It is also possible to calculate the average characteristics of two groups of people and analyze whether the two groups of people are separable. The accuracy of similarity calculation is improved through the method provided in the embodiment of the present invention.

[0121] Example 2

[0122] The embodiment of the present invention provides a finger ring glow image comparison system, such as Fig.14 As shown, including:

[0123] The inner and outer contour data acquisition module 1 is used to pre-process the finger image of the gas release imaging technology GDV of the first preset object, and use polar coordinate transformation to generate the inner and outer contours of each finger glow; this module executes the method described in step S1 of embodiment 1, which will not be repeated here.

[0124] The ellipse fitting module 2 is used to fit the ellipse shape according to the pixel points of the inner contour using the first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle of the ellipse; this module executes the method described in step S2 of embodiment 1, which will not be repeated here.

[0125] The finger direction positioning module 3 is used to locate the finger direction according to the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse and the rotation angle using a second preset function; this module executes the method described in step S3 of Example 1 and will not be repeated here.

[0126] The ring partitioning module 4 is used to partition the ring according to the finger direction; this module executes the method described in step S4 of embodiment 1, which will not be described in detail here.

[0127] The average thickness calculation module 5 is used to calculate the average thickness of the outer contour and inner contour of the entire finger glow image based on the entire finger glow image using the ordinates of the outer contour and inner contour after polar coordinate transformation; this module executes the method described in step S5 in embodiment 1 and will not be repeated here.

[0128] The histogram statistics module 6 is used to perform histogram statistics on each partition, and calculate the thickness value of the ring partition using the ordinates of the outer contour and the inner contour after polar coordinate transformation; this module executes the method described in step S6 of embodiment 1, which will not be repeated here.

[0129] The first preset defect detection module 7 is used to determine the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the ring partition; this module executes the method described in step S7 of embodiment 1, which will not be repeated here.

[0130] The second preset defect detection module 8 is used to repeat the inner and outer contour data acquisition module to the first preset defect detection module to determine the defect detection degree of the finger glow of the second preset object; this module executes the method described in step S8 in embodiment 1 and will not be repeated here.

[0131] The comparison module 9 is used to calculate the similarity between the first preset object and the second preset object according to the defect detection degree of the first preset finger glow and the defect detection degree of the finger glow of the second preset object; this module executes the method described in step S9 of embodiment 1 and will not be repeated here.

[0132] The embodiment of the present invention provides a finger ring glow image comparison system. For the ten finger glow images collected by the GDV device, the embodiment of the present invention proposes a finger ring glow image comparison system. This system can be used for finger glow image retrieval, that is, to find a person's finger glow image in the finger glow image library. It can also be used to compare with the average characteristics of a certain group of people. If a certain group of people have a certain disease that is displayed as a bulge or depression in a certain part of the finger ring, it can be inferred whether the current person being tested also has this disease with a high probability. The average characteristics of two groups of people can also be calculated to analyze whether the two groups of people are separable. The system provided by the present invention improves the accuracy of similarity calculation.

[0133] Example 3

[0134] An embodiment of the present invention provides a terminal, such as Fig.15As shown, it includes: at least one processor 401, such as a CPU (Central Processing Unit), at least one communication interface 403, a memory 404, and at least one communication bus 402. Among them, the communication bus 402 is used to realize the connection and communication between these components. Among them, the communication interface 403 may include a display screen (Display), a keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a wireless interface. The memory 404 may be a high-speed RAM memory (Random Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 404 may also be at least one storage device located away from the aforementioned processor 401. Among them, the processor 401 can execute the finger ring glow image comparison method in Example 1. A set of program codes are stored in the memory 404, and the processor 401 calls the program code stored in the memory 404 to execute the finger ring glow image comparison method in Example 1. The communication bus 402 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The communication bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.15 Only one line is used to represent it, but it does not mean that there is only one bus or one type of bus. Among them, the memory 404 may include a volatile memory (English: volatile memory), such as a random access memory (English: random-access memory, abbreviated: RAM); the memory may also include a non-volatile memory (English: non-volatile memory), such as a flash memory (English: flash memory), a hard disk drive (English: hard disk drive, abbreviated: HDD) or a solid-state drive (English: solid-state drive, abbreviated: SSD); the memory 404 may also include a combination of the above types of memory. Among them, the processor 401 may be a central processing unit (English: central processing unit, abbreviated: CPU), a network processor (English: network processor, abbreviated: NP) or a combination of CPU and NP.

[0135] Among them, the memory 404 may include a volatile memory (English: volatile memory), such as a random access memory (English: random-access memory, abbreviated: RAM); the memory may also include a non-volatile memory (English: non-volatile memory), such as a flash memory (English: flash memory), a hard disk drive (English: hard disk drive, abbreviated: HDD) or a solid-state drive (English: solid-state drive, abbreviated: SSD); the memory 404 may also include a combination of the above types of memory.

[0136] The processor 401 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and a NP.

[0137] The processor 401 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0138] Optionally, the memory 404 is also used to store program instructions. The processor 401 can call the program instructions to implement the finger ring glow image comparison method in the embodiment 1 of the present application.

[0139] The embodiment of the present invention further provides a computer-readable storage medium, on which computer-executable instructions are stored, and the computer-executable instructions can execute the finger ring glow image comparison method in embodiment 1. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0140] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the scope of protection of the invention.

Claims

1. A finger ring glow image comparison method, characterized in that: include: Preprocessing the finger image of the gas release imaging technology GDV of the first preset object, generating the inner contour and outer contour of each finger glow by polar coordinate transformation; According to the pixel points of the inner contour, the ellipse shape is fitted using a first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle; Locate the finger direction using a second preset function based on the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse, and the rotation angle; Divide the ring into zones according to the direction of the fingers; According to the entire finger glow image, the average thickness of the outer contour and the inner contour of the entire finger glow image is calculated using the ordinates of the outer contour and the inner contour after polar coordinate transformation; Perform histogram statistics on each partition, and use the ordinates of the outer and inner contours after polar coordinate transformation to calculate the thickness value of the ring partition; Determining the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the finger ring partition; Preprocessing the finger image of the gas release imaging technology GDV of the second preset object, and generating the inner contour and outer contour of each finger glow by polar coordinate transformation; According to the pixel points of the inner contour, the ellipse shape is fitted using a first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle; Locate the finger direction using a second preset function based on the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse, and the rotation angle; Divide the ring into zones according to the direction of the fingers; According to the entire finger glow image, the average thickness of the outer contour and the inner contour of the entire finger glow image is calculated using the ordinates of the outer contour and the inner contour after polar coordinate transformation; Perform histogram statistics on each partition, and use the ordinates of the outer and inner contours after polar coordinate transformation to calculate the thickness value of the ring partition; Determining the defect detection degree of the second preset finger glow according to the average thickness and the thickness value of the finger ring partition; The similarity between the first preset and the second preset objects is calculated according to the defect detection degree of the first preset finger glow and the defect detection degree of the finger glow of the second preset object.

2. The finger ring glow image comparison method according to claim 1, characterized in that: The first preset function includes: the fitEllipse function in opencv.

3. The finger ring glow image comparison method according to claim 1, characterized in that: According to the direction of the fingers, the ring is divided into zones, including: According to the finger direction, 360 degrees is divided into a first preset number of portions of a first preset angle, wherein the first preset number of portions is the number of zones of the ring zone.

4. The finger ring glow image comparison method according to claim 3, characterized in that: The average thickness of the outer contour and inner contour of the entire finger glow image is calculated by the following formula: in, represents the ordinate of the outer contour of the i-th point, It represents the ordinate of the inner contour of the i-th point, and N represents the number of points.

5. The finger ring glow image comparison method according to claim 1, characterized in that: Determining the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the ring partition includes: When the thickness value of the ring partition is larger than the mean value, the finger glow bulge is more serious; When the thickness value of the ring partition is smaller than the mean value, the finger glow depression is more serious.

6. The finger ring glow image comparison method according to claim 3, characterized in that: Partitioning the ring includes: partitioning each finger.

7. The finger ring glow image comparison method according to claim 1, characterized in that: The similarity between the first preset and the second preset objects is calculated by the following formula: Wherein, ab represents the first preset object and the second preset object respectively, a single finger partition is set to N parts, and the histogram of the current partition is 8. A finger ring glow image comparison system, characterized in that: include: The inner and outer contour data acquisition module is used to pre-process the finger image of the gas release imaging technology GDV of the first preset object, and generate the inner and outer contours of each finger glow by using polar coordinate transformation; An ellipse fitting module is used to fit the ellipse shape according to the pixel points of the inner contour by using a first preset function to generate the circumscribed rectangle of the ellipse, the major axis, the minor axis, the center point of the ellipse and the rotation angle; A finger direction positioning module, used to locate the finger direction using a second preset function according to the pixel points of the inner contour, the circumscribed rectangle, the major axis, the minor axis, the center point of the ellipse and the rotation angle of the ellipse; The ring partitioning module is used to partition the ring according to the finger direction; The average thickness calculation module is used to calculate the average thickness of the outer contour and the inner contour of the entire finger glow image according to the entire finger glow image using the ordinates of the outer contour and the inner contour after polar coordinate transformation; The histogram statistics module is used to perform histogram statistics on each partition and calculate the thickness value of the ring partition using the ordinates of the outer contour and inner contour after polar coordinate transformation; A first preset defect detection module, used to determine the defect detection degree of the first preset finger glow according to the average thickness and the thickness value of the ring partition; The second preset defect detection module repeats the inner and outer contour data acquisition module, the ellipse fitting module, the finger direction positioning module, the finger ring partitioning module, the average thickness calculation module, the histogram statistics module, and the first preset defect detection module for the finger image of the gas release imaging technology GDV of the second preset object to determine the defect detection degree of the finger glow of the second preset object; The comparison module calculates the similarity between the first preset object and the second preset object according to the defect detection degree of the first preset finger glow and the defect detection degree of the finger glow of the second preset object.

9. A terminal, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the finger ring glow image contrast method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the finger ring glow image comparison method according to any one of claims 1 to 7.

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