CN116864079A - Method, system and storage medium for measuring same body size of human body by transverse finger - Google Patents
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Abstract
The application provides a method for measuring the same size of a human body by transverse fingers, which comprises the following steps: s1, acquiring a hand image; s2, determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image; s3, drawing the finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points; s4, extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image; s5, searching for the pixel point coordinates on the outer side of the middle joint of the finger by adopting a traversing mode along the horizontal direction based on the pixel coordinate information of the key points of the finger joints and the pixel information of the edges of the hands, and determining the pixel point coordinates on the outer side of the middle joint of the finger; s6, calculating the finger size distance based on the coordinates of the pixel points on the outer sides of the middle joints of the fingers, and determining the same size of the human body transverse fingers. The application realizes accurate measurement of the same size of different human fingers.
Description
Technical Field
The application relates to the technical field of measurement of the same body size of human body transverse fingers, in particular to a method, a system and a storage medium for measuring the same body size of human body transverse fingers.
Background
The acupoints are the key points of the traditional Chinese medicine that the qi of the viscera and meridians is infused into the body surface, and are also one of the important points in the traditional Chinese medicine treatment. Acupuncture or moxibustion can activate qi in the channels and harmonize viscera to prevent and treat certain diseases. The accuracy of the location of the acupoints is directly related to the therapeutic effect of the acupoint therapy.
The same body size method of the finger is one of the common positioning methods of the acupoints in traditional Chinese medicine, and the clinical practice of the same body size method of the finger is usually that the doctor uses his finger to slightly stretch and contract according to subjective experience to perform specific positioning due to lack of measuring tools. Thus, positioning errors are large for patients with different body types, and treatment of different doctors for the same patient is different.
In order to solve the inaccuracy and the difference of the positioning of the acupoints, researchers have proposed to use elastic bands to realize personalized measurement of the same size of different body types, but the method has measurement errors caused by the difference of elastic coefficients of different elastic bands, and the same elastic band has measurement errors caused by the change of the elastic coefficients due to use loss.
Disclosure of Invention
The application provides a method, a system and a storage medium for measuring the same size of human body transverse fingers, which measure the same size of human body fingers through computer vision and image processing technology, thereby realizing individuation and accuracy of positioning different human body acupoints and laying a foundation for realizing automation and intellectualization of traditional Chinese medicine acupoint therapy.
The application aims to: the method is used for making up the current situation of lack of common body size detection tools in the current clinical traditional Chinese medicine acupoint treatment, providing a standard and reliable common body size detection technology for acupoint positioning, enabling the traditional Chinese medicine acupoint treatment to be more standardized, ensuring the curative effect of the traditional Chinese medicine acupoint treatment, simultaneously making the human body common body size data, and laying a foundation for research and development of the acupoint treatment medical robot.
In order to achieve the above purpose, the application adopts the following technical scheme:
the first aspect of the embodiments of the present specification discloses a method for measuring the same body size of a human body by transverse fingers, which comprises the following steps:
s1, acquiring a hand image;
s2, determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image;
s3, drawing the finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points;
s4, extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image;
s5, searching for the outer side pixel point coordinates of the middle joint in a traversing mode along the horizontal direction based on the finger joint key point pixel coordinate information and the hand edge pixel information, and determining the outer side pixel point coordinates of the middle joint;
s6, calculating the finger size distance based on the coordinates of the pixel points on the outer sides of the middle joints of the fingers, and determining the same size of the human body transverse fingers.
In some embodiments, in S1, a hand image inclination detection determination algorithm is used to determine whether the hand image is inclined, and if inclination is detected, the hand image is corrected.
In some embodiments, based on the knuckle key point pixel coordinate information, comparing magnitudes of leftmost and rightmost two-point abscissa values, if the leftmost abscissa value is greater than the rightmost abscissa value, the hand image is a back of hand image; if the left-most abscissa value is smaller than the right-most abscissa value, the hand image is a palm image; in the traversing process, the key points with smaller abscissa values are traversed along the horizontal negative direction, and the key points with larger abscissa values are traversed along the horizontal positive direction.
In some embodiments, traversing the hand edge pixels, judging whether the traversing is successful, if so, determining the coordinates of the pixel points outside the middle section; if not, judging whether the hand is successful or both sides of the hand are unsuccessful, if not, re-acquiring the hand image, and if not, expanding the traversal width of the unsuccessful side into the traversal width of the successful side.
A second aspect of embodiments of the present specification discloses a human body lateral-finger co-body measurement system comprising:
the hand image acquisition module is used for acquiring hand images;
the finger joint key point pixel coordinate information determining module is used for determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image;
the finger joint key point visualization module is used for drawing finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points;
the hand edge pixel information extraction module is used for extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image;
the finger middle section outside pixel point coordinate determining module is used for searching finger middle section outside pixel point coordinates in a traversing mode along the horizontal direction based on the finger joint key point pixel coordinate information and the hand edge pixel information and determining the finger middle section outside pixel point coordinates;
and the human body transverse finger same size determining module is used for calculating the finger size distance based on the coordinates of the pixel points outside the middle section of the finger and determining the human body transverse finger same size.
In some embodiments, the human transverse pointing system further comprises:
the processor is respectively connected with the hand image acquisition module, the finger joint key point pixel coordinate information determination module, the finger joint key point visualization module, the hand edge pixel information extraction module, the finger middle section outer side pixel point coordinate determination module and the human body transverse finger same size determination module;
a memory coupled to the processor and storing a computer program executable on the processor;
when the processor executes the computer program, the processor controls the hand image acquisition module, the finger joint key point pixel coordinate information determination module, the finger joint key point visualization module, the hand edge pixel information extraction module, the middle knuckle outer side pixel point coordinate determination module and the human body transverse finger same size determination module to work so as to realize the human body transverse finger same size measurement method.
A third aspect of the embodiments of the present specification discloses a computer-readable storage medium storing computer instructions that, when read by a computer, perform the human body lateral-identity measurement method as described above.
In summary, the application has at least the following advantages:
the application can be used for making an advantageous improvement for the current situation of lack of same-body measurement tools and methods in the treatment of acupoints in clinical traditional Chinese medicine, and secondly, standardizes and intellectuzes the same body size of human body transverse fingers, can improve the standardization and the accuracy of the positioning of the acupoints, ensures the treatment effect of the acupoints, and can further lay a feasible technical foundation for the research and the development of an acupoints treatment robot.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of steps of a method for measuring human body transverse orientation and identity according to the present application.
Fig. 2 is a schematic block diagram of a human body transverse orientation and body dimension measuring system according to the present application.
Fig. 3 is a schematic view of the same transverse dimensions as referred to in the present application.
Fig. 4 is a schematic diagram of a return example of the key point pixel coordinate information according to the present application.
Fig. 5 is a schematic diagram of a hand keypoint detection visualization according to the present application.
Fig. 6 is a schematic diagram of an edge detection image according to the present application.
Fig. 7 is a schematic diagram of an example of oblique hand image recognition according to the present application.
Fig. 8 is a schematic diagram of an example of palm detection errors in the present application.
Fig. 9 is a schematic diagram of a flow chart for detecting two sides of the middle node edge in the palm according to the present application.
Fig. 10 is a schematic view of rotations about different rotation centers according to the present application.
Fig. 11 is a schematic diagram of a rotational minimum external torque involved in the present application.
Fig. 12 is a schematic diagram of a flow of a traversal detection robustness enhancement algorithm according to the present application.
Fig. 13 is a schematic diagram of the overall flow of the system involved in the present application.
Fig. 14 is a schematic diagram of a user interface involved in the present application.
Detailed Description
Hereinafter, only certain exemplary embodiments are briefly described. As will be recognized by those of skill in the pertinent art, the described embodiments may be modified in numerous different ways without departing from the spirit or scope of the embodiments of the present application. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive.
The following disclosure provides many different implementations, or examples, for implementing different configurations of embodiments of the application. In order to simplify the disclosure of embodiments of the present application, components and arrangements of specific examples are described below. Of course, they are merely examples and are not intended to limit embodiments of the present application. Furthermore, embodiments of the present application may repeat reference numerals and/or letters in the various examples, which are for the purpose of brevity and clarity, and which do not themselves indicate the relationship between the various embodiments and/or arrangements discussed.
Embodiments of the present application will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a first aspect of the embodiments of the present specification discloses a method for measuring the same body size of a human body, including the following steps:
s1, acquiring a hand image;
s2, determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image;
s3, drawing the finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points;
s4, extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image;
s5, searching for the outer side pixel point coordinates of the middle joint in a traversing mode along the horizontal direction based on the finger joint key point pixel coordinate information and the hand edge pixel information, and determining the outer side pixel point coordinates of the middle joint;
s6, calculating the finger size distance based on the coordinates of the pixel points on the outer sides of the middle joints of the fingers, and determining the same size of the human body transverse fingers.
In some embodiments, in S1, a hand image inclination detection determination algorithm is used to determine whether the hand image is inclined, and if inclination is detected, the hand image is corrected.
In some embodiments, based on the knuckle key point pixel coordinate information, comparing magnitudes of leftmost and rightmost two-point abscissa values, if the leftmost abscissa value is greater than the rightmost abscissa value, the hand image is a back of hand image; if the left-most abscissa value is smaller than the right-most abscissa value, the hand image is a palm image; in the traversing process, the key points with smaller abscissa values are traversed along the horizontal negative direction, and the key points with larger abscissa values are traversed along the horizontal positive direction.
In some embodiments, traversing the hand edge pixels, judging whether the traversing is successful, if so, determining the coordinates of the pixel points outside the middle section; if not, judging whether the hand is successful or both sides of the hand are unsuccessful, if not, re-acquiring the hand image, and if not, expanding the traversal width of the unsuccessful side into the traversal width of the successful side.
As shown in fig. 2, a second aspect of the embodiments of the present specification discloses a human body lateral-finger co-body measurement system, comprising:
the hand image acquisition module is used for acquiring hand images;
the finger joint key point pixel coordinate information determining module is used for determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image;
the finger joint key point visualization module is used for drawing finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points;
the hand edge pixel information extraction module is used for extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image;
the finger middle section outside pixel point coordinate determining module is used for searching finger middle section outside pixel point coordinates in a traversing mode along the horizontal direction based on the finger joint key point pixel coordinate information and the hand edge pixel information and determining the finger middle section outside pixel point coordinates;
and the human body transverse finger same size determining module is used for calculating the finger size distance based on the coordinates of the pixel points outside the middle section of the finger and determining the human body transverse finger same size.
In some embodiments, the human transverse pointing system further comprises:
the processor is respectively connected with the hand image acquisition module, the finger joint key point pixel coordinate information determination module, the finger joint key point visualization module, the hand edge pixel information extraction module, the finger middle section outer side pixel point coordinate determination module and the human body transverse finger same size determination module;
a memory coupled to the processor and storing a computer program executable on the processor;
when the processor executes the computer program, the processor controls the hand image acquisition module, the finger joint key point pixel coordinate information determination module, the finger joint key point visualization module, the hand edge pixel information extraction module, the middle knuckle outer side pixel point coordinate determination module and the human body transverse finger same size determination module to work so as to realize the human body transverse finger same size measurement method.
A third aspect of the embodiments of the present specification discloses a computer-readable storage medium storing computer instructions that, when read by a computer, perform the human body lateral-identity measurement method as described above.
The inventive concept of the present application is as follows:
the same size of the transverse digits refers to the four digits of the index, middle, ring and little digits of a patient, the transverse dimension of the middle section of the middle finger is 3 inches, and the length of the four digits is 1.5 inches.
As shown in fig. 4, the key point pixel coordinate information returned after the finger joint key point detection algorithm is used, the algorithm is combined with the key point pixel coordinate information to draw the key point on the hand image, so that the key point detection visualization is realized, and the detection accuracy is ensured, as shown in fig. 5. Next, a differential edge detection algorithm is applied to the hand image, and hand edge pixels in the image are extracted as shown in fig. 6. Next, the program combines the key point pixel coordinate information and the hand edge pixel information, and adopts a traversing mode along the horizontal direction to search the pixel point coordinates on the outer side of the middle joint. Finally, calculating the pixel point A (x) at the outer side of the index finger joint by using the traversed coordinate information and using the formula (1) 1 ,y 1 ) And the lateral pixel point B (x) 2 ,y 2 ) The distance between the two fingers is then measured to obtain the same size p of the human body's transverse fingers.
The system can place hands in any direction when acquiring hand images, but coordinate points traversed in the horizontal direction are not lateral coordinates of the transverse lines of the middle joints, which appear when the inclined hand images are faced, as shown in the following figure 7. Therefore, the system designs a hand image inclination detection and judgment algorithm, the algorithm can automatically judge whether the hand image is inclined or not, and if the inclination is detected, the inclination image is corrected.
First, the position and coordinate information of 21 palm keypoints is acquired by using the existing palm keypoint detection algorithm. Fig. 5 is a visual effect diagram of coordinate point information output by a palm image according to an algorithm, wherein the numerical marks represent 21 main bone nodes of a hand, including finger tips and finger joints, and 6 'and 19' are points detected in traversal.
Second, edge detection is performed on the hand image, the RGB values of adjacent pixels of the regular area of the image are smooth, but at the edges of the image, abrupt changes with large differences in RGB values occur. The system therefore uses a difference algorithm (Difference Algorithm) to perform edge detection on the hand image. By traversing each pixel point of the image, comparing the differences of RGB values of adjacent pixels on the upper, lower, left and right sides, the point with larger difference is the edge pixel point, and the RGB value is truncated to be (255, 255, 255). The edge detection image is shown in fig. 6 below.
After acquiring the coordinate information of the key point pixels of the hand and the palm edge pixels based on the above steps, traversing each pixel point outwards along the horizontal direction of the index finger joint point 6 and the little finger joint point 19 to find the edge pixels with RGB values of (255, 255, 255), and acquiring the coordinate information of the pixel points, and acquiring the coordinate information of the outer sides of the index finger and the little finger middle section by the method so as to calculate the 3 inch pixel distance later. The same calculation methods for 1.5 inches and 1 inch can be implemented.
Considering that palm images comprise a back image and a palm image, in order to avoid the situation of wrong traversing directions as shown in fig. 7 and 8, the system designs a traversing search algorithm corresponding to the palm image and the back image. The algorithm firstly compares the X-axis pixel coordinate values X6 and X19 of the key points 6 and 19, judges that the image is a back hand image if X6 is larger than X19, and judges that the image is a palm hand image if X6 is smaller than X19. Before traversing, comparing the magnitudes of X6 and X19, wherein key points with smaller abscissa values are traversed along the negative X-axis direction, and key points with larger abscissa values are traversed along the positive X-axis direction. The specific steps of the algorithm are shown in fig. 9, and the correct detection of the hand image for both the palm and the back of the hand can be realized through the algorithm.
Subsequently, in order to avoid detection errors in edge detection, the pixel points traversed in traversing to find the coordinates of the palm edge points are not palm edge pixels, but are image edge pixel points. Thus, the traversal of the algorithm design in the horizontal direction does not traverse the entire image area, but only within the hand area, which may lead to a situation where no edge points are detected in the hand area. Therefore, the system designs a judging algorithm for judging whether the detection is successful or not, and the judging algorithm is divided into three cases of successful detection on both sides, successful detection on one side and unsuccessful detection on both sides. If the detection on both sides is successful, judging that the detection is successfully completed; if one side detection is successful, the algorithm sets the non-traversal detected one side expansion width to the detected other side value plus or minus 30 pixels offset, for example, the non-detection expansion width of the little finger is the expansion width of the index finger minus 30 pixels, and the non-detection expansion width of the index finger is the expansion width of the little finger plus 30 pixels. If the detection is successful, the detection fails, and the user is prompted to reintroduce a new hand image. The specific algorithm flow is shown in figure 12 below.
Meanwhile, the system also considers the condition that the acquired image is inclined in the palm, and in order to avoid detection errors caused by the condition, the system designs an inclination detection correction algorithm. The algorithm calculates the slope K between the two points according to the coordinate point information (X12, Y12) and (X0, Y0) of the key point 12 and the key point 0 by substituting the coordinate point information (X12, Y12) and the coordinate point information (X0, Y0) into the formula (2), and further obtains the inclination angle theta of the hand image according to the formula (3) by using the slope K. Next, the rotation center point of the image rotation is determined, and rotation is performed around the key point 0, the key point 12 and the middle point between the two points, as shown in fig. 10, it can be obtained that the situation that the hand area of the image is cut out in a large amount appears when the image rotates around the key point 0 and the key point 12, compared with the situation that the hand area is less influenced by the image after rotating around the middle point between the two key points, but the situation that the hand area is cut out still exists. In order to solve the problem, the system designs an algorithm for automatically updating the image curtain, and calculates coordinates of points A ', B', C ', D' after each point rotates according to four vertex coordinates A, B, C and D of the image by using a formula (4), so that the minimum external moment of the rotated image is shown in fig. 11, and the situation that the rotated image is cut out can be avoided by setting the image curtain to the minimum external moment during rotation.
θ＝arctanK(3)
Finally, after acquiring the coordinate information of the pixel points at the outer side of the middle node of the finger based on the flow operation, the algorithm calculates the Euclidean distance between the two points by using the formula (1), thereby calculating the same size of the finger of the human body.
To sum up, fig. 13 is a general algorithm flow chart of the system. Fig. 14 is a diagram of a system user interface, in which a user only needs to import a hand image, then click a finger size detection button, and the program can automatically detect and calculate the finger size, output a calculated value, and display a visual detection image on the interface, so that the user knows the detection effect. Fig. 5-8, 10, 11, and 14 are all screenshot of a system user interface, and are only for illustration, so as to facilitate understanding of the technical solution of the present application.
The above embodiments are provided to illustrate the present application and not to limit the present application, so that the modification of the exemplary values or the replacement of equivalent elements should still fall within the scope of the present application.
From the foregoing detailed description, it will be apparent to those skilled in the art that the present application can be practiced without these specific details, and that the present application meets the requirements of the patent statutes.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application. The foregoing description of the preferred embodiment of the application is not intended to be limiting, but rather to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the application.
It should be noted that the above description of the flow is only for the purpose of illustration and description, and does not limit the application scope of the present specification. Various modifications and changes to the flow may be made by those skilled in the art under the guidance of this specification. However, such modifications and variations are still within the scope of the present description.
While the basic concepts have been described above, it will be apparent to those of ordinary skill in the art after reading this application that the above disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements, and adaptations of the application may occur to one of ordinary skill in the art. Such modifications, improvements, and modifications are intended to be suggested within the present disclosure, and therefore, such modifications, improvements, and adaptations are intended to be within the spirit and scope of the exemplary embodiments of the present disclosure.
Meanwhile, the present application uses specific words to describe embodiments of the present application. For example, "one embodiment," "an embodiment," and/or "some embodiments" means a particular feature, structure, or characteristic in connection with at least one embodiment of the application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the application may be combined as suitable.
Furthermore, those of ordinary skill in the art will appreciate that aspects of the application are illustrated and described in the context of a number of patentable categories or conditions, including any novel and useful processes, machines, products, or materials, or any novel and useful improvements thereof. Accordingly, aspects of the present application may be implemented entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or a combination of hardware and software. The above hardware or software may be referred to as a "unit," module, "or" system. Furthermore, aspects of the present application may take the form of a computer program product embodied in one or more computer-readable media, wherein the computer-readable program code is embodied therein.
Computer program code required for operation of portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C ++, C#, VB.NET, python, etc., a conventional programming language such as C programming language, visualBasic, fortran2103, perl, COBOL2102, PHP, ABAP, a dynamic programming language such as Python, ruby and Groovy, or other programming languages, etc. The program code may execute entirely on the user's computer, or as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or the use of services such as software as a service (SaaS) in a cloud computing environment.
Furthermore, the order in which the elements and sequences are presented, the use of numerical letters, or other designations are used in the application is not intended to limit the sequence of the processes and methods unless specifically recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of example, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the application. For example, while the implementation of the various components described above may be embodied in a hardware device, it may also be implemented as a purely software solution, e.g., an installation on an existing server or mobile device.
Likewise, it should be noted that in order to simplify the presentation of the disclosure and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, the inventive subject matter should be provided with fewer features than the single embodiments described above.
Claims (7)
1. The method for measuring the same body size of the human body by transverse fingers is characterized by comprising the following steps of:
s1, acquiring a hand image;
s2, determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image;
s3, drawing the finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points;
s4, extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image;
s5, searching for the outer side pixel point coordinates of the middle joint in a traversing mode along the horizontal direction based on the finger joint key point pixel coordinate information and the hand edge pixel information, and determining the outer side pixel point coordinates of the middle joint;
s6, calculating the finger size distance based on the coordinates of the pixel points on the outer sides of the middle joints of the fingers, and determining the same size of the human body transverse fingers.
2. The method according to claim 1, wherein in S1, a hand image inclination detection determination algorithm is used to determine whether the hand image is inclined, and if inclination is detected, the hand image is corrected.
3. The method for measuring the same size of a human body transverse finger according to claim 1, wherein the sizes of the left-most and right-most two-point abscissa values are compared based on the pixel coordinate information of the finger joint key points, and if the left-most abscissa value is greater than the right-most abscissa value, the hand image is a back-of-hand image; if the left-most abscissa value is smaller than the right-most abscissa value, the hand image is a palm image; in the traversing process, the key points with smaller abscissa values are traversed along the horizontal negative direction, and the key points with larger abscissa values are traversed along the horizontal positive direction.
4. The method for measuring the same size of a human body transverse finger according to claim 1, wherein the method is characterized in that the edge pixels of the hand are traversed, whether the traversing is successful is judged, and if yes, the coordinates of pixel points outside the middle section of the finger are determined; if not, judging whether the hand is successful or both sides of the hand are unsuccessful, if not, re-acquiring the hand image, and if not, expanding the traversal width of the unsuccessful side into the traversal width of the successful side.
5. A human body lateral-finger same-size measurement system, comprising:
the hand image acquisition module is used for acquiring hand images;
the finger joint key point pixel coordinate information determining module is used for determining finger joint key point pixel coordinate information by using a finger joint key point detection algorithm based on the hand image;
the finger joint key point visualization module is used for drawing finger joint key points on the hand image based on the finger joint key point pixel coordinate information so as to visualize the finger joint key points;
the hand edge pixel information extraction module is used for extracting hand edge pixel information by using a differential edge detection algorithm based on the hand image;
the finger middle section outside pixel point coordinate determining module is used for searching finger middle section outside pixel point coordinates in a traversing mode along the horizontal direction based on the finger joint key point pixel coordinate information and the hand edge pixel information and determining the finger middle section outside pixel point coordinates;
and the human body transverse finger same size determining module is used for calculating the finger size distance based on the coordinates of the pixel points outside the middle section of the finger and determining the human body transverse finger same size.
6. The human body lateral co-body measurement system of claim 5, further comprising:
the processor is respectively connected with the hand image acquisition module, the finger joint key point pixel coordinate information determination module, the finger joint key point visualization module, the hand edge pixel information extraction module, the finger middle section outer side pixel point coordinate determination module and the human body transverse finger same size determination module;
a memory coupled to the processor and storing a computer program executable on the processor; when the processor executes the computer program, the processor controls the hand image acquisition module, the finger joint key point pixel coordinate information determination module, the finger joint key point visualization module, the hand edge pixel information extraction module, the finger middle section outer side pixel point coordinate determination module and the human body transverse finger same size determination module to work so as to realize the human body transverse finger same size measurement method according to any one of claims 1-4.
7. A computer-readable storage medium storing computer instructions that, when read by a computer, perform the human transverse orientation and identity measurement method according to any one of claims 1 to 4.
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