CN112070028B - Animal iris positioning method and system - Google Patents
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- 241001465754 Metazoa Species 0.000 title claims abstract description 63
- 238000000034 method Methods 0.000 title claims abstract description 29
- 210000001747 pupil Anatomy 0.000 claims abstract description 84
- 238000002372 labelling Methods 0.000 claims description 10
- 238000010276 construction Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 230000007547 defect Effects 0.000 abstract description 3
- 230000003321 amplification Effects 0.000 abstract 1
- 238000003199 nucleic acid amplification method Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 6
- 241000282465 Canis Species 0.000 description 3
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- 230000010339 dilation Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
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- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/193—Preprocessing; Feature extraction
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Abstract
The invention discloses an animal iris positioning method and system, wherein the positioning method comprises the following steps: acquiring iris images of animals; binarizing the iris image; tracking the binarized iris image by adopting a contour tracking algorithm, and determining the contour of each closed area of the binarized iris image; extracting characteristic parameters of the outline of each closed area; taking a closed area with the characteristic parameter within the pupil parameter threshold range as a pupil outline area; and amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal. After binarization processing is carried out on the iris image, the outline area of the pupil with higher identification degree is firstly obtained, then the outline area of the outer edge of the iris is obtained by amplification, the technical defect of inaccurate iris positioning caused by the problems of inclination, rotation, partial shielding and the like of the iris image is overcome, and the accuracy of animal iris outer edge positioning is improved.
Description
Technical Field
The invention relates to the technical field of animal management, in particular to an animal iris positioning method and an animal iris positioning system.
Background
Iris recognition is also a relatively more applied biological recognition technology, and has higher accuracy compared with fingerprint and face recognition technologies. The iris recognition technology is widely applied to the fields of finance, medical treatment, security check, security protection, attendance checking, entrance guard, industrial control and the like in special industries.
At present, animal management is mainly that a traditional RFID electronic tag is implanted into an animal body, so that the animal is injured to some extent, and a non-invasive iris recognition technology is adopted to recognize the identity of the animal, so that the animal management method has important significance.
The invention patent CN106326825A, CN101447025A discloses a method for positioning the outer edge of the iris, wherein the outer edge area of the iris is approximately circular, and a circular area is fitted on the iris image to be used as the outer edge area of the iris. However, compared with the human eye iris recognition technology, animal iris image recognition has the problems that an animal cannot actively cooperate with photographing like a human, so that collected images have inclination, rotation, partial shielding and the like, and the accurate iris outer edge is difficult to obtain by adopting the existing iris positioning technology, so that the iris recognition precision of the animal is influenced.
Disclosure of Invention
The invention aims to provide an animal iris positioning method and system so as to improve the accuracy of animal iris outer edge positioning.
In order to achieve the above object, the present invention provides the following solutions:
a method of positioning an iris of an animal, the method comprising the steps of:
acquiring iris images of animals;
performing binarization processing on the iris image to obtain a binarized iris image;
tracking the binarized iris image by adopting a contour tracking algorithm, and determining the contour of each closed area of the binarized iris image;
extracting characteristic parameters of the outline of each closed area;
setting a closed area of the characteristic parameter within a pupil parameter threshold range as a pupil outline area;
and amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal.
Optionally, the binarizing the iris image to obtain a binarized iris image further includes:
constructing a window with the size of k multiplied by k by taking the pixel point (i, j) as a center;
determining a threshold value of binarization processing of a pixel point (i, j) of the iris image within the window by using a formula t=m+c×s;
wherein m represents the average value of the gray values of all the pixel points in the window, s represents the variance of the gray values of all the pixel points in the window, and c is the adjustment parameter.
Optionally, the binarizing processing is performed on the iris image to obtain a binarized iris image, and then the method further includes:
expanding the binarized iris image to obtain an expanded iris image;
and labeling the iris image after expansion treatment in a reversing mode to obtain the label of each closed area of the iris image after binarization.
Optionally, the contour tracking algorithm is an eight-neighborhood contour tracking algorithm.
Optionally, the setting the closed area of the characteristic parameter within the pupil parameter threshold range as the contour area of the pupil specifically includes:
judging whether the area of the outline of the ith closed area is within the area threshold range of the pupil outline, whether the circularity of the outline of the ith closed area is larger than the circularity threshold of the pupil outline, whether the Solidity value of the outline of the ith closed area is larger than the Solidity value threshold of the through hole outline and whether the average gray level of the ith closed area is smaller than the gray level threshold of the pupil, and obtaining a judging result;
if the judgment result is yes, the ith closed area is the contour area of the pupil;
if the judgment result is negative, the ith closed area is not the contour area of the pupil.
An animal iris positioning system, the positioning system comprising:
the iris image acquisition module is used for acquiring iris images of animals;
the binarization processing module is used for performing binarization processing on the iris image to obtain a binarized iris image;
the contour tracking module is used for tracking the binarized iris image by adopting a contour tracking algorithm and determining the contour of each closed area of the binarized iris image;
the characteristic parameter extraction module is used for extracting characteristic parameters of the outline of each closed area;
the pupil outline region acquisition module is used for setting a closed region of the characteristic parameter within the pupil parameter threshold range as a pupil outline region;
and the amplifying module is used for amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal.
Optionally, the positioning system further comprises:
the window construction module is used for constructing a window with the size of k multiplied by k by taking the pixel point (i, j) as a center;
a threshold value determining module for binarizing, in the window, a threshold value of binarizing of the pixel point (i, j) of the iris image by using the formula t=m+c×s;
wherein m represents the average value of the gray values of all the pixel points in the window, s represents the variance of the gray values of all the pixel points in the window, and c is the adjustment parameter.
Optionally, the positioning system further comprises:
the expansion processing module is used for carrying out expansion processing on the binarized iris image to obtain an iris image after expansion processing;
the labeling processing module is used for labeling the iris image after expansion processing in a reversing mode to obtain labels of each closed area of the iris image after binarization.
Optionally, the contour tracking algorithm is an eight-neighborhood contour tracking algorithm.
Optionally, the pupil contour region acquiring module specifically includes:
the judging submodule is used for judging whether the area of the outline of the ith closed area is within the area threshold range of the pupil outline, whether the circularity of the outline of the ith closed area is larger than the circularity threshold of the pupil outline, whether the Solidity value of the outline of the ith closed area is larger than the Solidity value threshold of the through hole outline and whether the average gray level of the ith closed area is smaller than the gray level value threshold of the pupil or not, so as to obtain a judging result;
the pupil outline area determining submodule is used for determining that the ith closed area is the pupil outline area if the judgment result is yes; if the judgment result is negative, the ith closed area is not the contour area of the pupil.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses an animal iris positioning method and system, wherein the positioning method comprises the following steps: acquiring iris images of animals; performing binarization processing on the iris image to obtain a binarized iris image; tracking the binarized iris image by adopting a contour tracking algorithm, and determining the contour of each closed area of the binarized iris image; extracting characteristic parameters of the outline of each closed area; setting a closed area of the characteristic parameter within a pupil parameter threshold range as a pupil outline area; and amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal. After binarization processing is carried out on the acquired iris image, the outline area of the pupil with higher recognition degree is firstly acquired, then the outline area of the outer edge of the iris is obtained by enlarging, the technical defect of inaccurate iris positioning caused by the problems of inclination, rotation, partial shielding and the like of the iris image is overcome, and the accuracy of positioning the outer edge of the animal iris is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an animal iris positioning method provided by the invention;
fig. 2 is a flowchart of a canine iris positioning method according to an embodiment of the present invention;
fig. 3 is a schematic view of an outer edge contour region of a canine iris according to an embodiment of the present invention.
Detailed Description
The invention aims to provide an animal iris positioning method and system so as to improve the accuracy of animal iris outer edge positioning.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Referring to fig. 1, the invention provides a method for positioning an animal iris, which comprises the following steps:
step 101, obtaining iris images of animals;
and 102, performing binarization processing on the iris image to obtain a binarized iris image.
The binarizing processing is carried out on the iris image to obtain a binarized iris image, and the method further comprises the following steps: constructing a window with the size of k multiplied by k by taking the pixel point (i, j) as a center; determining a threshold value of binarization processing of a pixel point (i, j) of the iris image within the window by using a formula t=m+c×s; wherein m represents the average value of the gray values of all the pixel points in the window, s represents the variance of the gray values of all the pixel points in the window, and c is the adjustment parameter.
The binarizing processing is carried out on the iris image to obtain a binarized iris image, and then the method further comprises the following steps: expanding the binarized iris image to obtain an expanded iris image; and labeling the iris image after expansion treatment in a reversing mode to obtain the label of each closed area of the iris image after binarization.
Step 103, tracking the binarized iris image by adopting a contour tracking algorithm, and determining the contour of each closed area of the binarized iris image; the contour tracking algorithm is an eight-neighborhood contour tracking algorithm.
And 104, extracting characteristic parameters of the outline of each closed area. The characteristic parameters include: area, circularity, solidity value of the contour, and average gray scale of the closed region.
And 105, setting the closed area of the characteristic parameter within the pupil parameter threshold range as the contour area of the pupil.
Step 105, setting the closed area of the characteristic parameter within the pupil parameter threshold range as the contour area of the pupil specifically includes: judging whether the area of the outline of the ith closed area is within the area threshold range of the pupil outline, whether the circularity of the outline of the ith closed area is larger than the circularity threshold of the pupil outline, whether the Solidity value of the outline of the ith closed area is larger than the Solidity value threshold of the through hole outline and whether the average gray level of the ith closed area is smaller than the gray level threshold of the pupil, and obtaining a judging result; if the judgment result is yes, the ith closed area is the contour area of the pupil; if the judgment result is negative, the ith closed area is not the contour area of the pupil.
And 106, magnifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal.
The invention also provides an animal iris positioning system, which comprises:
the iris image acquisition module is used for acquiring iris images of animals;
the binarization processing module is used for performing binarization processing on the iris image to obtain a binarized iris image;
the contour tracking module is used for tracking the binarized iris image by adopting a contour tracking algorithm and determining the contour of each closed area of the binarized iris image; the contour tracking algorithm is an eight-neighborhood contour tracking algorithm.
The characteristic parameter extraction module is used for extracting characteristic parameters of the outline of each closed area;
and the pupil outline area acquisition module is used for setting the closed area of the characteristic parameter within the pupil parameter threshold range as the pupil outline area.
The pupil outline area acquisition module specifically comprises: the judging submodule is used for judging whether the area of the outline of the ith closed area is within the area threshold range of the pupil outline, whether the circularity of the outline of the ith closed area is larger than the circularity threshold of the pupil outline, whether the Solidity value of the outline of the ith closed area is larger than the Solidity value threshold of the through hole outline and whether the average gray level of the ith closed area is smaller than the gray level value threshold of the pupil or not, so as to obtain a judging result; the pupil outline area determining submodule is used for determining that the ith closed area is the pupil outline area if the judgment result is yes; if the judgment result is negative, the ith closed area is not the contour area of the pupil.
And the amplifying module is used for amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal.
As a preferred embodiment but not limited to this embodiment,
the positioning system further comprises: the window construction module is used for constructing a window with the size of k multiplied by k by taking the pixel point (i, j) as a center; a threshold value determining module for binarizing, in the window, a threshold value of binarizing of the pixel point (i, j) of the iris image by using the formula t=m+c×s; wherein m represents the average value of the gray values of all the pixel points in the window, s represents the variance of the gray values of all the pixel points in the window, and c is the adjustment parameter.
The positioning system further comprises: the expansion processing module is used for carrying out expansion processing on the binarized iris image to obtain an iris image after expansion processing; the labeling processing module is used for labeling the iris image after expansion processing in a reversing mode to obtain labels of each closed area of the iris image after binarization.
In order to illustrate the effects of the animal iris positioning method and system, the invention also provides a specific embodiment.
Referring to fig. 2, in step 201, an acquired iris image of a dog is opened, the height and width of the image are 1600 pixels and 900 pixels respectively, and after the image is read into a memory, the image is subjected to 2-valued by using a Niblack local 2-valued method. The Niblack local 2-valued method is that the mean and variance in the neighborhood with the pixel point as the center determine the 2-valued division threshold of the pixel together. And taking the pixel (i, j) as a center, and taking a window with the size of kxk, wherein the average value of gray values of all pixels in the window is m, and the variance is s, and the point threshold t is t=m+c×s, wherein c is an adjustment quantity parameter. For the iris image of this example, c is selected to be 0.2 and k is selected to be 15.
Step 202, after performing dilation processing on the 2-valued image, deleting a noise area with the area smaller than 200 pixels, inverting the 2-valued image, and then labeling to obtain a labeled image of the iris image.
Step 203, calling a contour tracing function to trace out contour lines corresponding to all the labels for the labeled images of the iris images obtained in step 202, and then calculating the area, the circularity and the quality value of all the contours. And obtaining the outline area of the outline edge of the iris according to the threshold values of the values.
In this example, the area threshold is set to be between 8000 pixels and 20000 pixels, the circularity is greater than 0.70, the resolution is greater than 0.82, the closed area with average gray scale less than 96 is the outline area of the outer edge of the canine iris, and the obtained outline area diagram is shown in fig. 3.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses an animal iris positioning method and system, wherein the positioning method comprises the following steps: acquiring iris images of animals; performing binarization processing on the iris image to obtain a binarized iris image; tracking the binarized iris image by adopting a contour tracking algorithm, and determining the contour of each closed area of the binarized iris image; extracting characteristic parameters of the outline of each closed area; setting a closed area of the characteristic parameter within a pupil parameter threshold range as a pupil outline area; and amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal. After binarization processing is carried out on the acquired iris image, the outline area of the pupil with higher recognition degree is firstly acquired, then the outline area of the outer edge of the iris is obtained by enlarging, the technical defect of inaccurate iris positioning caused by the problems of inclination, rotation, partial shielding and the like of the iris image is overcome, and the accuracy of positioning the outer edge of the animal iris is improved.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The principles and embodiments of the present invention have been described herein with reference to specific examples, which are intended to be only illustrative of the methods and concepts underlying the invention, and not all examples are intended to be within the scope of the invention as defined by the appended claims.
Claims (8)
1. An animal iris positioning method is characterized by comprising the following steps:
acquiring iris images of animals;
performing binarization processing on the iris image to obtain a binarized iris image;
tracking the binarized iris image by adopting a contour tracking algorithm, and determining the contour of each closed area of the binarized iris image;
extracting characteristic parameters of the outline of each closed area;
setting a closed area of the characteristic parameter within a pupil parameter threshold range as a pupil outline area;
amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal;
setting the closed area of the characteristic parameter within the pupil parameter threshold range as the contour area of the pupil, wherein the method specifically comprises the following steps:
judging whether the area of the outline of the ith closed area is within the area threshold range of the pupil outline, whether the circularity of the outline of the ith closed area is larger than the circularity threshold of the pupil outline, whether the Solidity value of the outline of the ith closed area is larger than the Solidity value threshold of the through hole outline and whether the average gray level of the ith closed area is smaller than the gray level threshold of the pupil, and obtaining a judging result;
if the judgment result is yes, the ith closed area is the contour area of the pupil;
if the judgment result is negative, the ith closed area is not the contour area of the pupil.
2. The method for positioning an animal iris according to claim 1, wherein said binarizing the iris image to obtain a binarized iris image, further comprising:
constructing a window with the size of k multiplied by k by taking the pixel point (i, j) as a center;
determining a threshold value of binarization processing of a pixel point (i, j) of the iris image within the window by using a formula t=m+c×s;
wherein m represents the average value of the gray values of all the pixel points in the window, s represents the variance of the gray values of all the pixel points in the window, and c is the adjustment parameter.
3. The method for positioning an animal iris according to claim 1, wherein the binarizing the iris image to obtain a binarized iris image, and further comprising:
expanding the binarized iris image to obtain an expanded iris image;
and labeling the iris image after expansion treatment in a reversing mode to obtain the label of each closed area of the iris image after binarization.
4. The method of claim 1, wherein the contour tracking algorithm is an eight neighborhood contour tracking algorithm.
5. An animal iris positioning system, the positioning system comprising:
the iris image acquisition module is used for acquiring iris images of animals;
the binarization processing module is used for performing binarization processing on the iris image to obtain a binarized iris image;
the contour tracking module is used for tracking the binarized iris image by adopting a contour tracking algorithm and determining the contour of each closed area of the binarized iris image;
the characteristic parameter extraction module is used for extracting characteristic parameters of the outline of each closed area;
the pupil outline region acquisition module is used for setting a closed region of the characteristic parameter within the pupil parameter threshold range as a pupil outline region;
the amplifying module is used for amplifying the outline area of the pupil according to the average ratio of the pupil to the iris of the animal to obtain the outline area of the outer edge of the iris of the animal;
the pupil outline area acquisition module specifically comprises:
the judging submodule is used for judging whether the area of the outline of the ith closed area is within the area threshold range of the pupil outline, whether the circularity of the outline of the ith closed area is larger than the circularity threshold of the pupil outline, whether the Solidity value of the outline of the ith closed area is larger than the Solidity value threshold of the through hole outline and whether the average gray level of the ith closed area is smaller than the gray level value threshold of the pupil or not, so as to obtain a judging result;
the pupil outline area determining submodule is used for determining that the ith closed area is the pupil outline area if the judgment result is yes; if the judgment result is negative, the ith closed area is not the contour area of the pupil.
6. The animal iris positioning system of claim 5, wherein the positioning system further comprises:
the window construction module is used for constructing a window with the size of k multiplied by k by taking the pixel point (i, j) as a center;
a threshold value determining module for binarizing, in the window, a threshold value of binarizing of the pixel point (i, j) of the iris image by using the formula t=m+c×s;
wherein m represents the average value of the gray values of all the pixel points in the window, s represents the variance of the gray values of all the pixel points in the window, and c is the adjustment parameter.
7. The animal iris positioning system of claim 5, wherein the positioning system further comprises:
the expansion processing module is used for carrying out expansion processing on the binarized iris image to obtain an iris image after expansion processing;
the labeling processing module is used for labeling the iris image after expansion processing in a reversing mode to obtain labels of each closed area of the iris image after binarization.
8. The animal iris positioning system of claim 5, wherein the contour tracking algorithm is an eight neighborhood contour tracking algorithm.
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| 基于分块搜索的虹膜定位算法;刘帅等;计算机工程与应用;20170824;第54卷(第18期);212-217 * |
| 虹膜定位算法的研究;史春蕾;金龙旭;;计算机科学;20100915(第09期);270-272 * |
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