CN113435377A - Medical palm vein image acquisition monitoring method and system - Google Patents

Medical palm vein image acquisition monitoring method and system Download PDF

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CN113435377A
CN113435377A CN202110761588.2A CN202110761588A CN113435377A CN 113435377 A CN113435377 A CN 113435377A CN 202110761588 A CN202110761588 A CN 202110761588A CN 113435377 A CN113435377 A CN 113435377A
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image
vein
pixel
palm
palm vein
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吴国军
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Abstract

The invention relates to the technical field of image acquisition, and discloses a medical palm vein image acquisition monitoring method, which comprises the following steps: emitting infrared light by using an LED to irradiate the palm, collecting the reflected infrared light by using an image sensor, and carrying out graying and linear stretching treatment on the collected image to obtain a palm vein image; processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image; carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein blood vessel image; and (4) deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database. The invention also provides a medical palm vein image acquisition monitoring system. The invention realizes the acquisition of medical vein images.

Description

Medical palm vein image acquisition monitoring method and system
Technical Field
The invention relates to the technical field of image acquisition, in particular to a medical palm vein image acquisition monitoring method and system.
Background
How to safely and efficiently identify the identity of an individual is an important problem which must be solved in the information era. The traditional identity identification method, such as an identity card, a user name and the like, has the defects that the identity card, the user name and the like are easy to lose and leak, and the like, which cannot be overcome, and the requirement of keeping the identity of the user secret in the medical field is more and more difficult to meet, and under the background, the biometric feature identification technology comes into force.
Palm vein identification is an emerging biological feature identification technology, and has many advantages, such as that palm veins belong to internal features of a body, have vitality, and are identified in a non-contact manner. As such, palm vein identification is becoming a focus of increasing attention.
The traditional vein image acquisition method extracts a small number of vein endpoints and vein intersections, and simultaneously acquires a low contrast vein image.
In view of this, how to acquire a vein image with higher quality becomes an urgent problem to be solved by those skilled in the art.
Disclosure of Invention
The invention provides a medical palm vein image acquisition monitoring method, which comprises the steps of irradiating a palm by using an LED to emit infrared light, acquiring reflected infrared light by using an image sensor to obtain a palm vein image, and processing the acquired palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image; and carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein image, simultaneously carrying out deburring and thinning processing on the vein image, and storing the processed vein image into a medical database.
In order to achieve the above object, the present invention provides a medical palm vein image acquisition monitoring method, which comprises:
emitting infrared light by using an LED to irradiate the palm, collecting the reflected infrared light by using an image sensor, and carrying out graying and linear stretching treatment on the collected image to obtain a palm vein image;
processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image;
carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein blood vessel image;
and (4) deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database.
Optionally, the illuminating the palm with the infrared light emitted by the LED, and collecting the reflected infrared light by the image sensor, includes:
irradiating the palm with infrared light emitted by the LED, wherein in one specific embodiment of the invention, the wavelength of the emitted infrared light is 780 nm;
the infrared light penetrates through tissues and enters blood vessels, hemoglobin in the vein blood vessels absorbs the near infrared light, other palm tissues reflect the near infrared light, the reflected light returns to the image sensor, and the image sensor collects the reflected light to obtain a palm vein image with a bright background and a dark target.
Optionally, the graying and linear stretching processing of the acquired image includes:
1) solving the maximum value of three components of each pixel in the collected palm vein image, and setting the maximum value as the gray value of the pixel point to obtain the gray image of the palm vein image, wherein the formula of the graying treatment is as follows:
G(i,j)＝max{R(i,j),G(i,j),B(i,j)}
wherein:
(i, j) is a pixel point in the palm vein image;
r (i, j), G (i, j) and B (i, j) are respectively the values of the pixel point (i, j) in R, G, B three color channels;
g (i, j) is the gray value of the pixel point (i, j);
2) for the gray-scale image, the gray scale of the image is linearly stretched by utilizing a piecewise linear transformation mode, and the formula is as follows:
Figure BDA0003150061200000021
wherein:
f (x, y) is a gray value of the gray image;
MAXf(x,y),MINf(x,y)respectively the maximum and minimum grey values of the grey map.
Optionally, the processing the collected palm vein image by using a histogram equalization method includes:
1) dividing the palm vein image into M continuous and non-overlapping subregions;
2) calculating a gray level histogram of each subregion;
3) calculate the average number of pixels per sub-region:
Figure BDA0003150061200000022
wherein:
m represents the total number of pixels in the sub-region;
l represents the number of gray levels of the sub-region;
set the enhancement threshold to
Figure BDA0003150061200000023
Making the gray level histogram of the subarea larger than
Figure BDA0003150061200000024
Truncating the pixel number, adding the truncated pixel number, and averagely distributing the pixel number to each gray level;
4) calculating the probability of the occurrence of each gray level pixel in each sub-region gray level histogram after distribution:
Figure BDA0003150061200000025
wherein:
i represents a gray level, and L gray levels are total;
nirepresenting the number of pixels with the gray level i in the sub-area;
m represents the total number of pixels in the sub-region;
Pia probability of occurrence of a pixel representing a gray level i in the sub-region;
5) performing histogram equalization processing on each subarea:
Figure BDA0003150061200000026
wherein:
Pja probability of occurrence of a pixel representing a gray level j in the sub-region;
i' represents the gray level after histogram equalization processing;
obtaining a balanced subregion image;
6) and combining the equalized subarea images to obtain an image-enhanced palm vein image.
Optionally, the performing, by using a vein image segmentation algorithm based on vein curvature, a segmentation process on the palm vein image includes:
1) calculating the curvature k of the palm vein image at different direction angles thetaθ：
Figure BDA0003150061200000027
Figure BDA0003150061200000028
d′θ＝d′xcosθ+d′ycosθ
Figure BDA0003150061200000029
Figure BDA0003150061200000031
Figure BDA0003150061200000032
Figure BDA0003150061200000033
Figure BDA0003150061200000034
Wherein:
(x, y) represents coordinates of the palm vein image;
d′θa first directional derivative representing a palm vein image;
d″θrepresenting the second directional derivative of the palm vein image;
in one embodiment of the present invention, the selected directional angle is 45 °;
2) detecting kθThe detected local maximum point is taken as Q ═ Q1,q2,…,qnN is the number of detected local maximum points; for detected local maximum points qiIn the neighborhood of (2), counting the number N (q) of continuous pixels with curvature value larger than 0i) And calculating the score of the local maximum point:
S(qi)＝k(qi)*N(qi)
wherein:
k(qi) Denotes qiA curvature value of;
storing the scores of all local maximum points in a matrix F;
3) in the matrix F, respectively finding a pixel point (x, y), two pixel points adjacent to the left side of the pixel point and two pixel points adjacent to the right side of the pixel point; if the value of the pixel point (x, y) is smaller than or larger than the values of the two adjacent 4 pixel points, increasing or decreasing the value of the pixel point (x, y), and horizontally connecting the 5 pixel points, wherein the formula for increasing or decreasing the value of the pixel point (x, y) is as follows:
G(x,y)＝min{max(F(x+1),y),F(x+2,y)),max(F(x-1),y),F(x-2,y))}
wherein:
g (x, y) is the pixel value of the pixel (x, y) after enhancement or reduction;
processing all pixel values to obtain a vein blood vessel image based on curvature;
4) and carrying out binarization processing on the vein image based on the curvature, selecting a threshold value T, marking pixel points smaller than the threshold value T in the vein image based on the curvature as a background, and marking the rest pixel points as veins to obtain the vein image.
Optionally, the deburring and thinning processing on the vein blood vessel image includes:
1) carrying out corrosion treatment on the vein blood vessel image pixel matrix:
Figure BDA0003150061200000035
wherein:
a represents a vein blood vessel image pixel matrix;
(x, y) represents image pixels;
b represents the erosion matrix, which in one embodiment of the invention is:
Figure BDA0003150061200000036
b is sequentially moved on A, when the image element (x, y) of A is translated, if the image element (x, y) of B is completely contained in the overlapped area of the image A, namely the corresponding A image value of the element position of 1 in B is all 1, the image element (x, y) corresponding to the output image is assigned to 1, otherwise, the image element (x, y) is assigned to 0;
2) expanding the pixel matrix of the corroded vein blood vessel image:
Figure BDA0003150061200000037
wherein:
a' represents a pixel matrix of the vein blood vessel image after corrosion;
c denotes the expansion matrix, which in one embodiment of the invention is used:
Figure BDA0003150061200000041
translating B to an image pel (x, y) position; if the intersection of the B and the A 'at the image pixel (x, y) is not empty, namely at least one image value corresponding to the A' at the element position of 1 in the B is 1, the pixel (x, y) corresponding to the output image is assigned to be 1, otherwise, the pixel is assigned to be 0;
3) detecting all vein endpoints and intersections of the vein blood vessel image after expansion processing, starting from a certain vein endpoint i, searching the intersections or endpoints along vein lines, marking pixel points between the intersections or endpoints, counting the number, and marking as M; 4) setting a threshold value T, if M is less than T, considering that the vein endpoint i is a burr, and setting the marked pixel point as a background; otherwise, the vein is regarded as the vein endpoint, and the marked pixel point is reserved;
5) and 3) performing the step 4) on all vein end points to obtain the vein vessel image after deburring and thinning.
In addition, in order to achieve the above object, the present invention further provides a medical palm vein image acquisition monitoring system, including:
the image acquisition device is used for irradiating the palm with infrared light emitted by the LED and collecting the reflected infrared light through the image sensor;
the image processor is used for carrying out graying and linear stretching processing on the acquired image to obtain a palm vein image; processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image;
the medical palm vein image acquisition device is used for carrying out segmentation processing on a palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein blood vessel image; and (4) deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database.
In addition, to achieve the above object, the present invention also provides a computer readable storage medium, which stores thereon medical palm vein image acquisition program instructions executable by one or more processors to implement the steps of the implementation method of medical palm vein image acquisition monitoring as described above.
Compared with the prior art, the invention provides a medical palm vein image acquisition monitoring method, which has the following advantages:
first, the conventional image contrast enhancement method is a histogram equalization method, which equalizes the number of pixels per gray level, i.e., there are no large number of similar pixels, the contrast of the image is improved, since the number of pixels of the image is fixed, in order to make the number of pixels of each gray level equal, it is necessary to make the gray level of the image span a wider range of gray levels, for example, the histogram equalization method may equalize pixels with gray levels of 0-4 to gray levels of 1-3, and if the number of pixels in 0, 4 gray levels is small, the number of pixels with 0 and 4 gray levels is set to be null, but when the gray level of the image is more, the traditional histogram equalization method can obviously reduce the gray level of the image, so that the vein detail information of the palm image is lost, therefore, the invention improves the traditional histogram equalization method, and the improved histogram equalization method comprises the following processes: dividing the palm vein image into M continuous and non-overlapping subregions; calculating a gray level histogram of each subregion; calculate the average number of pixels per sub-region:
Figure BDA0003150061200000042
wherein: m represents the total number of pixels in the sub-region; l represents the number of gray levels of the sub-region; set the enhancement threshold to
Figure BDA0003150061200000043
Making the gray level histogram of the subarea larger than
Figure BDA0003150061200000044
Is truncated to limit the image contrast, and the truncated pixel numbers are added to average the scoreAssigning each gray level to ensure that all gray levels have higher pixel number and the pixel number difference of each gray level is reduced; calculating the probability of the occurrence of each gray level pixel in each sub-region gray level histogram after distribution:
Figure BDA0003150061200000045
wherein: i represents a gray level, and L gray levels are total; n isiRepresenting the number of pixels with the gray level i in the sub-area; m represents the total number of pixels in the sub-region; piA probability of occurrence of a pixel representing a gray level i in the sub-region; performing histogram equalization processing on each subarea:
Figure BDA0003150061200000051
wherein: pjA probability of occurrence of a pixel representing a gray level j in the sub-region; i' represents the gray level after histogram equalization processing; obtaining a balanced subregion image; and combining the equalized subarea images to obtain an image-enhanced palm vein image. Compared with the traditional algorithm, the improved algorithm provided by the invention has the advantages that the pixel number of the image is truncated, the truncated pixel numbers are added and averagely distributed to each gray level, so that the pixel number difference of each gray level is reduced, and the problem that the image gray level is obviously reduced to cause the loss of the detail of the palm vein image during the histogram equalization can be avoided.
Meanwhile, the invention provides a vein image segmentation algorithm based on vein curvature, which firstly calculates the curvature k of the palm vein image at different direction angles thetaθ：
Figure BDA0003150061200000052
Figure BDA0003150061200000053
d′θ＝d′xcosθ+d′ycosθ
Figure BDA0003150061200000054
Figure BDA0003150061200000055
Figure BDA0003150061200000056
Figure BDA0003150061200000057
Figure BDA0003150061200000058
Wherein: (x, y) represents coordinates of the palm vein image; d'θA first directional derivative representing a palm vein image; d ″)θRepresenting the second directional derivative of the palm vein image; by detecting curvature kθThe detected local maximum point is taken as Q ═ Q1,q2,…,qnAnd n is the number of local maximum points detected, since the vein curve in the palm vein image is a concave curve, the lowest point of the concave curve is the center point of the vein, the curvature of the lowest point of the concave curve is the maximum, and the value with the curvature greater than 0 in the concave curve is the vein, for the palm vein image, the pixel point with the maximum curvature may be the center point of the vein, and Q is { Q ═ Q { (Q) } Q { (Q) for the palm vein image, where the value with the maximum curvature is the value of the vein, and the value with the maximum curvature is the value of the lowest point of the concave curve1,q2,…,qnThe candidate pixel points are the vein central point candidate pixel points of the palm image; for detected local maximum points qiIn the neighborhood of (2), counting the number N (q) of continuous pixels with curvature value larger than 0i) And calculating the score of the local maximum point:
S(qi)＝k(qi)*N(qi)
wherein: k (q)i) Denotes qiA curvature value of; storing the scores of all local maximum points in a matrix F; because of the interference of factors such as burrs and noise, the detected local maximum point may not be the true vein central point, and this local maximum point needs to be eliminated, therefore in the matrix F, the pixel point (x, y) and the two pixel points adjacent to the left side and the two pixel points adjacent to the right side are found respectively, if the value of the pixel point (x, y) is less than or greater than the value of the 4 pixel points adjacent to the two sides, the value of the pixel point (x, y) is increased or reduced, and these 5 pixel points are horizontally connected, that is, the vein central point is connected, the connection result is the vein, the formula for increasing or reducing the value of the pixel point (x, y) is:
G(x,y)＝min{max(F(x+1),y),F(x+2,y)),max(F(x-1),y),F(x-2,y))}
wherein: g (x, y) is the pixel value of the pixel (x, y) after enhancement or reduction; processing all pixel values to obtain a vein blood vessel image based on curvature; the invention carries out cross-section processing on a palm vein image, expresses the position of a pixel point on a cross-section line and the gray value of the pixel point in a Cartesian coordinate system, finds that the gray curve of a vein area is a concave curve, the lowest point of the concave curve is the center point of a vein, the curvature of the lowest point of the concave curve is the maximum, the value with the curvature larger than 0 in the concave curve is the vein, and for the palm vein image, the pixel point with the maximum curvature is probably the center point of the vein, therefore, the invention uses the value with the maximum curvature in a local palm vein image as a candidate pixel point at the center of the vein by detecting the curvature of the image gray curve, calculates the number of pixel points with the curvature larger than 0 around the candidate pixel point at the center of the vein, calculates the score of the candidate pixel point at the center of each vein, and carries out denoising and deburring on each pixel point in the score matrix F, the method comprises the steps of selecting values of pixel points, namely the values of the pixel points are smaller than or larger than values of 4 adjacent pixel points on two sides, increasing or reducing the values of the pixel points, horizontally connecting the 5 pixel points, namely connecting vein central points, wherein the connection result is a vein vessel, so that vein labeling in a palm vein image is realized.
Drawings
Fig. 1 is a schematic flow chart of a medical palm vein image acquisition monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a medical palm vein image acquisition and monitoring system according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Emitting infrared light by using an LED to irradiate the palm, collecting the reflected infrared light by using an image sensor to obtain a palm vein image, and processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image; and carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein image, simultaneously carrying out deburring and thinning processing on the vein image, and storing the processed vein image into a medical database. Fig. 1 is a schematic view of a medical palm vein image acquisition monitoring method according to an embodiment of the present invention.
In this embodiment, the medical palm vein image acquisition monitoring method includes:
and S1, emitting infrared light by an LED to irradiate the palm, collecting the reflected infrared light by an image sensor, and carrying out graying and linear stretching processing on the collected image to obtain a palm vein image.
Firstly, the invention uses LED to emit infrared light to irradiate the palm, and in a specific embodiment of the invention, the wavelength of the emitted infrared light is 780 nm;
infrared light penetrates through tissues and enters blood vessels, hemoglobin in vein blood vessels absorbs near infrared light, other palm tissues reflect the near infrared light, the reflected light returns to an image sensor, and the image sensor collects the reflected light to obtain a palm vein image with a bright background and a dark target;
further, the invention performs graying and grayscale stretching processing on the collected palm vein image, and the flow of the image graying and grayscale stretching processing is as follows:
1) solving the maximum value of three components of each pixel in the collected palm vein image, and setting the maximum value as the gray value of the pixel point to obtain the gray image of the palm vein image, wherein the formula of the graying treatment is as follows:
G(i,j)＝max{R(i,j),G(i,j),B(i,j)}
wherein:
(i, j) is a pixel point in the palm vein image;
r (i, j), G (i, j) and B (i, j) are respectively the values of the pixel point (i, j) in R, G, B three color channels;
g (i, j) is the gray value of the pixel point (i, j);
2) for the gray-scale image, the gray scale of the image is linearly stretched by utilizing a piecewise linear transformation mode, and the formula is as follows:
Figure BDA0003150061200000061
wherein:
f (x, y) is a gray value of the gray image;
MAXf(x,y),MINf(x,y)respectively the maximum and minimum grey values of the grey map.
And S2, processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image.
Furthermore, the invention adopts a histogram equalization method to enhance the collected palm vein image, and the flow of the histogram equalization method is as follows:
1) dividing the palm vein image into M continuous and non-overlapping subregions;
2) calculating a gray level histogram of each subregion;
3) calculate the average number of pixels per sub-region:
Figure BDA0003150061200000071
wherein:
m represents the total number of pixels in the sub-region;
l represents the number of gray levels of the sub-region;
set the enhancement threshold to
Figure BDA0003150061200000072
Making the gray level histogram of the subarea larger than
Figure BDA0003150061200000073
Truncating the pixel number, adding the truncated pixel number, and averagely distributing the pixel number to each gray level;
4) calculating the probability of the occurrence of each gray level pixel in each sub-region gray level histogram after distribution:
Figure BDA0003150061200000074
wherein:
i represents a gray level, and L gray levels are total;
nirepresenting the number of pixels with the gray level i in the sub-area;
m represents the total number of pixels in the sub-region;
Pia probability of occurrence of a pixel representing a gray level i in the sub-region;
5) performing histogram equalization processing on each subarea:
Figure BDA0003150061200000075
wherein:
Pja probability of occurrence of a pixel representing a gray level j in the sub-region;
i' represents the gray level after histogram equalization processing;
obtaining a balanced subregion image;
6) and combining the equalized subarea images to obtain an image-enhanced palm vein image.
And S3, carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on the vein curvature to obtain a vein blood vessel image.
Furthermore, the invention utilizes a vein image segmentation algorithm based on vein curvature to segment the palm vein image, and the vein image segmentation algorithm based on vein curvature comprises the following steps:
1) calculating the curvature k of the palm vein image at different direction angles thetaθ：
Figure BDA0003150061200000076
Figure BDA0003150061200000077
d′θ＝d′xcosθ+d′ycosθ
Figure BDA0003150061200000078
Figure BDA0003150061200000081
Figure BDA0003150061200000082
Figure BDA0003150061200000083
Figure BDA0003150061200000084
Wherein:
(x, y) represents coordinates of the palm vein image;
d′θa first directional derivative representing a palm vein image;
d″θrepresenting the second directional derivative of the palm vein image;
in one embodiment of the present invention, the selected directional angle is 45 °;
2) detecting kθThe detected local maximum point is taken as Q ═ Q1,q2,…,qnN is the number of detected local maximum points; for detected local maximum points qiIn the neighborhood of (2), counting the number N (q) of continuous pixels with curvature value larger than 0i) And calculating the score of the local maximum point:
S(qi)＝k(qi)*N(qi)
wherein:
k(qi) Denotes qiA curvature value of;
storing the scores of all local maximum points in a matrix F;
3) in the matrix F, respectively finding a pixel point (x, y), two pixel points adjacent to the left side of the pixel point and two pixel points adjacent to the right side of the pixel point; if the value of the pixel point (x, y) is smaller than or larger than the values of the two adjacent 4 pixel points, increasing or decreasing the value of the pixel point (x, y), and horizontally connecting the 5 pixel points, wherein the formula for increasing or decreasing the value of the pixel point (x, y) is as follows:
G(x,y)＝min{max(F(x+1),y),F(x+2,y)),max(F(x-1),y),F(x-2,y))}
wherein:
g (x, y) is the pixel value of the pixel (x, y) after enhancement or reduction;
processing all pixel values to obtain a vein blood vessel image based on curvature;
4) and carrying out binarization processing on the vein image based on the curvature, selecting a threshold value T, marking pixel points smaller than the threshold value T in the vein image based on the curvature as a background, and marking the rest pixel points as veins to obtain the vein image.
And S4, deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database.
Further, the invention carries out deburring and thinning processing on the vein blood vessel image, and the deburring and thinning processing method of the vein blood vessel image comprises the following steps:
1) carrying out corrosion treatment on the vein blood vessel image pixel matrix:
Figure BDA0003150061200000085
wherein:
a represents a vein blood vessel image pixel matrix;
(x, y) represents image pixels;
b represents the erosion matrix, which in one embodiment of the invention is:
Figure BDA0003150061200000086
b is sequentially moved on A, when the image element (x, y) of A is translated, if the image element (x, y) of B is completely contained in the overlapped area of the image A, namely the corresponding A image value of the element position of 1 in B is all 1, the image element (x, y) corresponding to the output image is assigned to 1, otherwise, the image element (x, y) is assigned to 0;
2) expanding the pixel matrix of the corroded vein blood vessel image:
Figure BDA0003150061200000091
wherein:
a' represents a pixel matrix of the vein blood vessel image after corrosion;
c denotes the expansion matrix, which in one embodiment of the invention is used:
Figure BDA0003150061200000092
translating B to an image pel (x, y) position; if the intersection of the B and the A 'at the image pixel (x, y) is not empty, namely at least one image value corresponding to the A' at the element position of 1 in the B is 1, the pixel (x, y) corresponding to the output image is assigned to be 1, otherwise, the pixel is assigned to be 0;
3) detecting all vein endpoints and intersections of the vein blood vessel image after expansion processing, starting from a certain vein endpoint i, searching the intersections or endpoints along vein lines, marking pixel points between the intersections or endpoints, counting the number, and marking as M;
4) setting a threshold value T, if M is less than T, considering that the vein endpoint i is a burr, and setting the marked pixel point as a background; otherwise, the vein is regarded as the vein endpoint, and the marked pixel point is reserved;
5) and 3) performing the step 4) on all vein end points to obtain the vein vessel image after deburring and thinning.
Further, the present invention stores the vein image of the deburred and refined vein image in a medical database.
The following describes embodiments of the present invention through an algorithmic experiment and tests of the inventive treatment method. The hardware test environment of the algorithm of the invention is as follows: inter (R) core (TM) i7-6700KCPU with software Matlab2018 b; the contrast method is a medical palm vein image acquisition method based on random forests and a medical palm vein image acquisition method based on sensors.
In the algorithm experiment, the data set is 10G of medical palm vein images to be acquired. In the experiment, the medical palm vein image to be acquired is acquired by using the medical image acquisition method, the quality of the acquired image is used as an evaluation index of algorithm feasibility, and the higher the quality of the acquired medical palm vein image is, the higher the effectiveness and the feasibility of the algorithm are.
According to the experimental result, the image quality of the medical palm vein image acquisition method based on the sensor is 84.62%, the image quality of the medical palm vein image acquisition method based on the neural network is 87.66%, the image quality of the method is 90.11%, and compared with a comparison algorithm, the medical palm vein image acquisition monitoring method provided by the invention can acquire a medical palm vein image with higher quality.
The invention also provides a medical palm vein image acquisition monitoring system. Fig. 2 is a schematic diagram of an internal structure of a medical palm vein image acquisition and monitoring system according to an embodiment of the present invention.
In the present embodiment, the medical palm vein image acquisition monitoring system 1 includes at least an image acquisition device 11, an image processor 12, a medical palm vein image acquisition device 13, a communication bus 14, and a network interface 15.
The image capturing device 11 may be a PC (Personal Computer), a terminal device such as a smart phone, a tablet Computer, or a mobile Computer, or may be a server.
Image processor 12 includes at least one type of readable storage medium including flash memory, a hard disk, a multi-media card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The image processor 12 may in some embodiments be an internal storage unit of the medical palm vein image acquisition monitoring system 1, for example a hard disk of the medical palm vein image acquisition monitoring system 1. The image processor 12 may also be an external storage device of the medical palm vein image acquisition monitoring system 1 in other embodiments, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like provided on the medical palm vein image acquisition monitoring system 1. Further, the image processor 12 may also include both an internal storage unit and an external storage device of the medical palm vein image capture monitoring system 1. The image processor 12 may be used not only to store application software installed in the medical palm vein image capture monitoring system 1 and various types of data, but also to temporarily store data that has been output or is to be output.
The medical palm vein image capture device 13 may be, in some embodiments, a Central Processing Unit (CPU), controller, microcontroller, microprocessor or other data Processing chip including a monitoring Unit for running program code stored in the image processor 12 or Processing data, such as medical palm vein image capture program instructions 16.
The communication bus 14 is used to enable connection communication between these components.
The network interface 15 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), and is typically used to establish a communication link between the system 1 and other electronic devices.
Optionally, the medical palm vein image acquisition monitoring system 1 may further include a user interface, the user interface may include a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further include a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display may also be referred to as a display screen or a display unit, where appropriate, for displaying information processed in the medical palm vein image acquisition monitoring system 1 and for displaying a visual user interface.
Fig. 2 only shows the medical palm vein image acquisition monitoring system 1 with the components 11-15, and it will be understood by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the medical palm vein image acquisition monitoring system 1, and may include fewer or more components than those shown, or some components in combination, or a different arrangement of components.
In the embodiment of the medical palm vein image acquisition monitoring system 1 shown in fig. 2, the image processor 12 stores therein medical palm vein image acquisition program instructions 16; the steps of the medical palm vein image acquisition device 13 executing the medical palm vein image acquisition program instructions 16 stored in the image processor 12 are the same as the implementation method of the medical palm vein image acquisition monitoring method, and are not described here.
Furthermore, an embodiment of the present invention also provides a computer-readable storage medium having stored thereon medical palm vein image acquisition program instructions executable by one or more processors to implement the following operations:
emitting infrared light by using an LED to irradiate the palm, collecting the reflected infrared light by using an image sensor, and carrying out graying and linear stretching treatment on the collected image to obtain a palm vein image;
processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image;
carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein blood vessel image;
and (4) deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database.
It should be noted that the above-mentioned numbers of the embodiments of the present invention are merely for description, and do not represent the merits of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (8)

1. A medical palm vein image acquisition monitoring method is characterized by comprising the following steps:
emitting infrared light by using an LED to irradiate the palm, collecting the reflected infrared light by using an image sensor, and carrying out graying and linear stretching treatment on the collected image to obtain a palm vein image;
processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image;
carrying out segmentation processing on the palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein blood vessel image;
and (4) deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database.
2. The medical palm vein image acquisition monitoring method according to claim 1, wherein the illuminating the palm with the infrared light emitted by the LED and collecting the reflected infrared light by the image sensor comprises:
irradiating the palm with infrared light emitted by the LED;
the infrared light penetrates through tissues and enters blood vessels, hemoglobin in the vein blood vessels absorbs the near infrared light, other palm tissues reflect the near infrared light, the reflected light returns to the image sensor, and the image sensor collects the reflected light to obtain a palm vein image with a bright background and a dark target.
3. The medical palm vein image acquisition monitoring method according to claim 2, wherein the graying and linear stretching processing of the acquired image comprises:
1) solving the maximum value of three components of each pixel in the collected palm vein image, and setting the maximum value as the gray value of the pixel point to obtain the gray image of the palm vein image, wherein the formula of the graying treatment is as follows:
G(i，j)＝max{R(i，j)，G(i，j)，B(i，j)}
wherein:
(i, j) is a pixel point in the palm vein image;
r (i, j), G (i, j) and B (i, j) are respectively the values of the pixel point (i, j) in R, G, B three color channels;
g (i, j) is the gray value of the pixel point (i, j);
2) for the gray-scale image, the gray scale of the image is linearly stretched by utilizing a piecewise linear transformation mode, and the formula is as follows:
Figure FDA0003150061190000011
wherein:
f (x, y) is a gray value of the gray image;
MAXf(x，y)，MINf(x，y)respectively the maximum and minimum grey values of the grey map.
4. The medical palm vein image acquisition monitoring method according to claim 3, wherein the processing the acquired palm vein image by using the histogram equalization method comprises:
1) dividing the palm vein image into M continuous and non-overlapping subregions;
2) calculating a gray level histogram of each subregion;
3) calculate the average number of pixels per sub-region:
Figure FDA0003150061190000012
wherein:
m represents the total number of pixels in the sub-region;
l represents the number of gray levels of the sub-region;
set the enhancement threshold to
Figure FDA0003150061190000013
Making the gray level histogram of the subarea larger than
Figure FDA0003150061190000014
Truncating the pixel number, adding the truncated pixel number, and averagely distributing the pixel number to each gray level;
4) calculating the probability of the occurrence of each gray level pixel in each sub-region gray level histogram after distribution:
Figure FDA0003150061190000015
wherein:
i represents a gray level, and L gray levels are total;
nirepresenting the number of pixels with the gray level i in the sub-area;
m represents the total number of pixels in the sub-region;
Pia probability of occurrence of a pixel representing a gray level i in the sub-region;
5) performing histogram equalization processing on each subarea:
Figure FDA0003150061190000021
wherein:
Pja probability of occurrence of a pixel representing a gray level j in the sub-region;
i' represents the gray level after histogram equalization processing;
obtaining a balanced subregion image;
6) and combining the equalized subarea images to obtain an image-enhanced palm vein image.
5. The medical palm vein image acquisition monitoring method according to claim 4, wherein the palm vein image segmentation processing by using the vein image segmentation algorithm based on vein curvature comprises:
1) calculating the curvature k of the palm vein image at different direction angles thetaθ：
Figure FDA0003150061190000022
Figure FDA0003150061190000023
d′θ＝d′xcosθ+d′ycosθ
Figure FDA0003150061190000024
Figure FDA0003150061190000025
Figure FDA0003150061190000026
Figure FDA0003150061190000027
Figure FDA0003150061190000028
Wherein:
(x, y) represents coordinates of the palm vein image;
d′θa first directional derivative representing a palm vein image;
d″θrepresenting the second directional derivative of the palm vein image;
2) detecting kθThe detected local maximum point is taken as Q ═ Q1，q2，...，qnN is the number of detected local maximum points; for detected local maximum points qiIn the neighborhood of (2), counting the number N (q) of continuous pixels with curvature value larger than 0i) And calculating the score of the local maximum point:
S(qi)＝k(qi)*N(qi)
wherein:
k(qi) Denotes qiA curvature value of;
storing the scores of all local maximum points in a matrix F;
3) in the matrix F, respectively finding a pixel point (x, y), two pixel points adjacent to the left side of the pixel point and two pixel points adjacent to the right side of the pixel point; if the value of the pixel point (x, y) is smaller than or larger than the values of the two adjacent 4 pixel points, increasing or decreasing the value of the pixel point (x, y), and horizontally connecting the 5 pixel points, wherein the formula for increasing or decreasing the value of the pixel point (x, y) is as follows:
G(x，y)＝min{max(F(x+1)，y)，F(x+2，y))，max(F(x-1)，y)，F(x-2，y))}
wherein:
g (x, y) is the pixel value of the pixel (x, y) after enhancement or reduction;
processing all pixel values to obtain a vein blood vessel image based on curvature;
4) and carrying out binarization processing on the vein image based on the curvature, selecting a threshold value T, marking pixel points smaller than the threshold value T in the vein image based on the curvature as a background, and marking the rest pixel points as veins to obtain the vein image.
6. The medical palm vein image acquisition monitoring method according to claim 5, wherein the deburring and thinning processing on the vein blood vessel image comprises the following steps:
1) carrying out corrosion treatment on the vein blood vessel image pixel matrix:
Figure FDA0003150061190000031
wherein:
a represents a vein blood vessel image pixel matrix;
(x, y) represents image pixels;
b represents a corrosion matrix, and the adopted corrosion matrix is as follows:
Figure FDA0003150061190000032
b is sequentially moved on A, when the image element (x, y) of A is translated, if the image element (x, y) of B is completely contained in the overlapped area of the image A, namely the corresponding A image value of the element position of 1 in B is all 1, the image element (x, y) corresponding to the output image is assigned to 1, otherwise, the image element (x, y) is assigned to 0;
2) expanding the pixel matrix of the corroded vein blood vessel image:
Figure FDA0003150061190000033
wherein:
a' represents a pixel matrix of the vein blood vessel image after corrosion;
c represents the expansion matrix, the expansion matrix used is:
Figure FDA0003150061190000034
translating B to an image pel (x, y) position; if the intersection of the B and the A 'at the image pixel (x, y) is not empty, namely at least one image value corresponding to the A' at the element position of 1 in the B is 1, the pixel (x, y) corresponding to the output image is assigned to be 1, otherwise, the pixel is assigned to be 0;
3) detecting all vein endpoints and intersections of the vein blood vessel image after expansion processing, starting from a certain vein endpoint i, searching the intersections or endpoints along vein lines, marking pixel points between the intersections or endpoints, counting the number, and marking as M;
4) setting a threshold value T, if M is less than T, considering that the vein endpoint i is a burr, and setting the marked pixel point as a background; otherwise, the vein is regarded as the vein endpoint, and the marked pixel point is reserved;
5) and 3) performing the step 4) on all vein end points to obtain the vein vessel image after deburring and thinning.
7. A medical palm vein image acquisition monitoring system, the system comprising:
the image acquisition device is used for irradiating the palm with infrared light emitted by the LED and collecting the reflected infrared light through the image sensor;
the image processor is used for carrying out graying and linear stretching processing on the acquired image to obtain a palm vein image; processing the collected palm vein image by adopting a histogram equalization method to obtain an image-enhanced palm vein image;
the medical palm vein image acquisition device is used for carrying out segmentation processing on a palm vein image by using a vein image segmentation algorithm based on vein curvature to obtain a vein blood vessel image; and (4) deburring and thinning the vein blood vessel image, and storing the processed vein blood vessel image into a medical database.
8. A computer readable storage medium having stored thereon medical palm vein image acquisition program instructions executable by one or more processors to implement the steps of an implementation method of medical palm vein image acquisition monitoring as described above.
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