CN110781747A - Eyelash occlusion area pre-detection method based on coefficient of variation - Google Patents

Eyelash occlusion area pre-detection method based on coefficient of variation Download PDF

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CN110781747A
CN110781747A CN201910899748.2A CN201910899748A CN110781747A CN 110781747 A CN110781747 A CN 110781747A CN 201910899748 A CN201910899748 A CN 201910899748A CN 110781747 A CN110781747 A CN 110781747A
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iris
area
block
eyelashes
shielded
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叶学义
陈妍婷
季毕胜
陈泽
魏阳洋
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Hangzhou Dianzi University
Hangzhou Electronic Science and Technology University
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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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    • 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
    • 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
    • G06V40/197—Matching; Classification

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Abstract

The invention discloses a method for pre-detecting an eyelash occlusion area based on a coefficient of variation. The method comprises the steps of firstly partitioning upper and lower regions of an iris, then calculating the variation coefficient of the upper and lower blocks which are symmetrical about the center of the iris, judging whether the blocks on the iris are shielded by eyelashes or not by comparing the variation coefficients of the upper and lower blocks, judging whether each block on the iris is shielded by eyelashes or not by comparing the gray distribution difference of the upper and lower blocks of the iris, and carrying out region integration on the blocks on the iris which are shielded by eyelashes to obtain an eyelash shielding region. The method of the invention is used for predetermining the distribution range of eyelashes in the iris area, thus shortening the search range of later-stage eyelash detection, improving the detection efficiency and reducing the false eyelash detection rate.

Description

Eyelash occlusion area pre-detection method based on coefficient of variation
Technical Field
The invention belongs to the field of biological feature identification and information security, and particularly relates to a method for pre-detecting an eyelash occlusion area based on a coefficient of variation.
Background
The development of the iris recognition technology forms a complete framework system, but the key factor for determining and influencing the iris recognition performance is the acquisition quality of the iris. Under the state that human eyes are naturally opened, due to physiological structure, iris collection is difficult to avoid the influence of eyelash shading, and has diversity, so that eyelash detection is the core problem of iris identification performance limit improvement or iris flooding detection.
At present, the relevant research aiming at eyelash detection is mostly to realize eyelash detection through threshold segmentation or morphological knowledge on the whole iris area. Mask uses the gray difference between eyelashes and surrounding irises to set a threshold value for achieving the purpose of eyelash detection. (mask libor. recognition of Human Iris Patterns for biometrical identification [ D ].2003.) Oedist, etc. by using morphological knowledge, obtain Iris image with histogram having segmentation characteristic through gray-scale opening operation, and detect eyelash through binarization. (Leiye, Luchenhong, Luchaoyang. eyelid and eyelash occlusion detection for iris recognition [ J ] computer aided design and graphics newspaper.) Yangxiang adopts a self-adaptive double-threshold segmentation method to detect eyelashes, and flexibly adjusts the threshold according to the illumination conditions of different images. (study on Yangxingsheng iris image preprocessing and feature coding methods [ D ] 2016), all the methods can realize eyelash detection to a certain extent, but because eyelash regions are not determined in advance, the later search range is too large, the detection efficiency is low, and eyelash false detection is serious.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for pre-detecting an eyelash occlusion area based on a coefficient of variation. The method comprises the steps of firstly partitioning upper and lower iris areas, then adopting the coefficient of variation as a criterion, judging whether each iris partition is shielded by eyelashes or not by comparing the gray distribution difference of the upper and lower iris partition areas, and finally performing area integration on the partitions to obtain the eyelash shielding areas.
A method for pre-detecting an eyelash occlusion area based on a coefficient of variation comprises the following steps:
and (1) taking the center of the iris as an origin to perform equal-radian fan-shaped partitioning on the iris area.
And (2) judging whether each iris block is shielded by eyelashes or not, respectively calculating the variation coefficients of the upper and lower blocks which are symmetrical about the center of the iris circle, and if the variation coefficient of the upper block is larger than that of the lower block, and the difference value between the variation coefficient of the upper block and that of the lower block is larger than or equal to a set threshold Thr (Thr is larger than or equal to 0 and smaller than or equal to 0.15), the upper block is shielded by the eyelashes, and if the difference value is not larger than the set threshold Thr, the upper block is not shielded by the eyelashes.
Step (3) dividing the upper half of the iris into block areas I 1And integrating the partitioned areas internally shielded by the eyelashes to obtain an eyelash shielding area.
The method comprises the following specific steps:
dividing the iris into n (n is an even number) blocks by taking the center of the iris as an origin and theta radian (theta is more than or equal to 5 and less than or equal to 20) at intervals, and dividing the block into block areas S i＝[(i-1)×θ,i×θ]I ═ 1,2, …, n; upper half of iris block area I 1Including a block area S iI1, 2, …, n/2, the inferior semi-iris block region I 2Including a block area S i，i＝n/2+1,n/2+2,…,n。
Step (2), for example, the specific method is as follows:
calculating blocks S on the iris 1With sub-iris blocks symmetrical about the center of the iris
Figure BDA0002211432850000021
The specific formula of the coefficient of variation of (a) is as follows; f (p, q) represents the pixel value of the pixel point at the p-th row and the q-th column in the block. N is a radical of 1Representing blocks S on the iris 1The number of the pixel points in the display screen, representing sub-iris patches
Figure BDA0002211432850000023
The number of internal pixel points;
calculating S 1Mean value of inner gray level mu 1；
Figure BDA0002211432850000024
Computing
Figure BDA0002211432850000025
Mean value of inner gray
Figure BDA0002211432850000026
Calculating S 1Gray scale standard deviation V within a region 1：
Figure BDA0002211432850000032
Computing
Figure BDA0002211432850000033
Standard deviation of gray scale in area
Figure BDA0002211432850000035
Calculating S 1Coefficient of variation CV within a region 1；
Figure BDA0002211432850000036
Computing
Figure BDA0002211432850000037
Coefficient of variation within a region
Figure BDA0002211432850000038
Figure BDA0002211432850000039
When in use
Figure BDA00022114328500000310
Block area S on temporal iris 1Is shielded by eyelashes;
when in use
Figure BDA00022114328500000311
Block area S on temporal iris 1Is not shielded by eyelashes.
The specific method comprises the following steps:
firstly, judging a block area S 1Whether or not it is shielded by eyelashes, when the area is divided into blocks 1When not shielded by eyelashes, judging the next block area S 2If the first partitioned area is shielded by eyelashes, repeating the steps until the first partitioned area shielded by eyelashes is detected, stopping judging, and marking the first partitioned area as S T1(ii) a Then judging the block area S n/2Whether or not it is shielded by eyelashes, when the area is divided into blocks n/2When not shielded by eyelashes, judging the next block area S n/2-1 whether it is obstructed by eyelashes, and so on, until the first blocked area obstructed by eyelashes is detected, the decision is stopped and it is marked as S T2(ii) a Finally, the block area S T1、S T2And integrating the partitioned areas between the two to obtain an eyelash shading area.
The invention has the following beneficial effects:
the method solves the problems that the eyelash area is not determined in advance, so that the later searching range is too large, the detection efficiency is low, and the eyelash false detection condition is serious in the prior art. The method of the invention is used for predetermining the distribution range of eyelashes in the iris area, thus shortening the search range of later-stage eyelash detection, improving the detection efficiency and reducing the false eyelash detection rate.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
As shown in FIG. 1, the method of the present invention comprises the following steps:
a method for pre-detecting an eyelash occlusion area based on a coefficient of variation comprises the following steps:
taking the center of an iris circle as an origin, and carrying out equal-radian fan-shaped partitioning on the iris area:
dividing the iris into n (n is an even number) blocks by taking the center of the iris as an origin and theta radian (theta is more than or equal to 5 and less than or equal to 20) at intervals, and dividing the block into block areas S i＝[(i-1)×θ,i×θ]I ═ 1,2, …, n; upper half of iris block area I 1Including a block area S iI1, 2, …, n/2, the inferior semi-iris block region I 2Including a block area S i，i＝n/2+1,n/2+2,…,n。
And (2) judging whether each iris block is shielded by eyelashes or not, respectively calculating the variation coefficients of the upper and lower blocks which are symmetrical about the center of the iris circle, and if the variation coefficient of the upper block is larger than that of the lower block, and the difference value between the variation coefficient of the upper block and that of the lower block is larger than or equal to a set threshold Thr (Thr is larger than or equal to 0 and smaller than or equal to 0.15), the upper block is shielded by the eyelashes, and if the difference value is not larger than the set threshold Thr, the upper block is not shielded by the eyelashes.
For example, the specific method is as follows:
calculating the iris upper partition S1 and the iris lower partition symmetric about the center of the iris
Figure BDA0002211432850000041
The specific formula of the coefficient of variation of (a) is as follows; f (p, q) represents the pixel value of the pixel point at the p-th row and the q-th column in the block. N is a radical of 1Representing blocks S on the iris 1Number of inner pixels, N 2I 1Representing sub-iris patches
Figure BDA0002211432850000051
The number of internal pixel points;
calculating S 1Mean value of inner gray level mu 1；
Figure BDA0002211432850000052
Computing Mean value of inner gray
Figure BDA0002211432850000054
Figure BDA0002211432850000055
Calculating S 1Gray scale standard deviation V within a region 1：
Figure BDA0002211432850000056
Computing
Figure BDA0002211432850000057
Standard deviation of gray scale in area
Figure BDA0002211432850000058
Calculating S 1Coefficient of variation CV within a region 1；
Figure BDA00022114328500000510
Computing
Figure BDA00022114328500000511
Coefficient of variation within a region
Figure BDA00022114328500000512
Figure BDA00022114328500000513
When in use
Figure BDA00022114328500000514
Block area S on temporal iris 1Is shielded by eyelashes;
when in use
Figure BDA0002211432850000061
Block area S on temporal iris 1Is not shielded by eyelashes.
Step (3) dividing the upper half of the iris into block areas I 1Integrating the blocked areas blocked by the eyelashes to obtain an eyelash blocking area:
firstly, judging a block area S 1Whether or not it is shielded by eyelashes, when the area is divided into blocks 1When not shielded by eyelashes, judging the next block area S 2If the first partitioned area is shielded by eyelashes, repeating the steps until the first partitioned area shielded by eyelashes is detected, stopping judging, and marking the first partitioned area as S T1(ii) a Then judging the block area S n/2Whether or not it is shielded by eyelashes, when the area is divided into blocks n/2When not shielded by eyelashes, judging the next block area S n/2-1 whether it is obstructed by eyelashes, and so on, until the first blocked area obstructed by eyelashes is detected, the decision is stopped and it is marked as S T2(ii) a Finally, the block area S T1、S T2And integrating the partitioned areas between the two to obtain an eyelash shading area.

Claims (4)

1. A method for pre-detecting an eyelash occlusion area based on a coefficient of variation is characterized by comprising the following steps:
taking the center of an iris circle as an origin, and carrying out equal-radian fan-shaped partitioning on an iris area;
step (2), judging whether each iris upper block is shielded by eyelashes or not, respectively calculating the variation coefficients of the upper and lower blocks which are symmetrical about the center of the iris circle, and if the variation coefficient of the upper block is larger than that of the lower block, and the difference value between the variation coefficient of the upper block and that of the lower block is larger than or equal to a set threshold value Thr, (0-Thr is larger than or equal to 0.15), judging that the upper block is shielded by the eyelashes, and if the difference value is not larger than the set threshold value Thr, judging that the upper block is not shielded by the eyelashes;
step (3) dividing the upper half of the iris into block areasI 1And integrating the partitioned areas internally shielded by the eyelashes to obtain an eyelash shielding area.
2. The method for pre-detecting the eyelash occlusion area based on the coefficient of variation as claimed in claim 1, wherein the step (1) is as follows:
dividing the iris into n (n is an even number) blocks by taking the center of the iris as an origin and theta radian (theta is more than or equal to 5 and less than or equal to 20) at intervals, and dividing the block into block areas S i＝[(i-1)×θ,i×θ]I ═ 1,2, …, n; upper half of iris block area I 1Including a block area S iI1, 2, …, n/2, the inferior semi-iris block region I 2Including a block area S i，i＝n/2+1,n/2+2,…,n。
3. The method for pre-detecting the eyelash occlusion area based on the coefficient of variation as claimed in claim 2, wherein the step (2) is as follows:
calculating blocks S on the iris 1With sub-iris blocks symmetrical about the center of the iris The specific formula of the coefficient of variation of (a) is as follows; f (p, q) represents the pixel values of pixel points at the p-th row and the q-th column in the block; n is a radical of 1Representing blocks S on the iris 1Number of inner pixels, N 2I 1Representing sub-iris patches
Figure FDA0002211432840000012
The number of internal pixel points;
calculating S 1Mean value of inner gray level mu 1；
Figure FDA0002211432840000013
Computing
Figure FDA0002211432840000014
Mean value of inner gray
Figure FDA0002211432840000015
Figure FDA0002211432840000021
Calculating S 1Gray scale standard deviation V within a region 1：
Figure FDA0002211432840000022
Computing
Figure FDA0002211432840000023
Standard deviation of gray scale in area
Figure FDA0002211432840000024
Figure FDA0002211432840000025
Calculating S 1Coefficient of variation CV within a region 1；
Figure FDA0002211432840000026
Computing
Figure FDA0002211432840000027
Coefficient of variation within a region
Figure FDA0002211432840000028
When in use
Figure FDA00022114328400000210
Block area S on temporal iris 1Is shielded by eyelashes;
when in use
Figure FDA00022114328400000211
Block area S on temporal iris 1Is not shielded by eyelashes.
4. The method for pre-detecting the eyelash occlusion area based on the coefficient of variation as claimed in claim 3, wherein the specific method of step (3) is as follows:
firstly, judging a block area S 1Whether or not it is shielded by eyelashes, when the area is divided into blocks 1When not shielded by eyelashes, judging the next block area S 2If the first partitioned area is shielded by eyelashes, repeating the steps until the first partitioned area shielded by eyelashes is detected, stopping judging, and marking the first partitioned area as S T1(ii) a Then judging the block area S n/2Whether or not it is shielded by eyelashes, when the area is divided into blocks n/2When not shielded by eyelashes, judging the next block area S n/2-1Whether the first partitioned area is shielded by the eyelashes or not is determined by analogy until the first partitioned area shielded by the eyelashes is detected, the judgment is stopped, and the first partitioned area is marked as S T2(ii) a Finally, the block area S T1、S T2And integrating the partitioned areas between the two to obtain an eyelash shading area.
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