CN110619273A - Efficient iris recognition method and device - Google Patents
Efficient iris recognition method and device Download PDFInfo
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- CN110619273A CN110619273A CN201910747973.4A CN201910747973A CN110619273A CN 110619273 A CN110619273 A CN 110619273A CN 201910747973 A CN201910747973 A CN 201910747973A CN 110619273 A CN110619273 A CN 110619273A
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000004364 calculation method Methods 0.000 claims abstract description 12
- 238000007781 pre-processing Methods 0.000 claims abstract description 11
- 238000007689 inspection Methods 0.000 claims description 27
- 238000012545 processing Methods 0.000 claims description 24
- 238000001914 filtration Methods 0.000 claims description 9
- 238000003709 image segmentation Methods 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 6
- 238000003708 edge detection Methods 0.000 claims description 6
- 230000011218 segmentation Effects 0.000 claims description 4
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- 230000037430 deletion Effects 0.000 description 1
- 230000013020 embryo development Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
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- 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
- G06V40/19—Sensors therefor
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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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- 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 an efficient iris recognition method and a recognition device, wherein the recognition method comprises the steps of collecting a plurality of human eye images, and defining the collected human eye images as initial images; judging whether the initial image meets the identification requirement or not, and deleting the initial image which does not meet the identification requirement; carrying out image preprocessing operation on the initial image; obtaining an iris area in each initial image, and segmenting the iris area from the initial images to obtain a plurality of images to be detected; and identifying and matching the multiple images to be detected with prestored iris images stored in a database. Before iris extraction and identification matching are carried out on the initial image, a deleting step is introduced, and the initial image which does not meet the identification requirement is deleted, so that the calculation amount caused by subsequent identification matching on the initial image is greatly reduced, and the identification efficiency of the iris identification process is improved.
Description
Technical Field
The present invention relates to the field of image recognition technology, and more particularly, to an iris recognition method and device.
Background
Currently in the field of identification, human iris recognition has gradually replaced fingerprint recognition because the iris of human eyes has uniqueness and stability, the iris formation of each person is mainly determined by the embryonic development environment, so that two eyes with completely the same iris structure do not exist, and the iris texture is stably formed after eight months of birth of a human and does not change for life.
A large number of technical schemes for human iris recognition exist in the prior art, and the traditional iris recognition mainly comprises the steps of collecting a plurality of iris images, preprocessing each iris image, extracting an iris area and recognizing and matching the iris. The iris recognition technical scheme in the prior art has low efficiency, which is mainly because the existing iris recognition technology needs to perform a series of operations such as subsequent iris extraction, recognition matching and the like on each acquired iris image, and the completion of the whole recognition overshoot is not finished until a certain iris image is successfully recognized and matched with data stored in a database, so that the calculation amount of the whole iris recognition process is huge, and the efficiency is low. If the image screening step can be introduced in the earlier stage of the iris identification process, the whole iris identification process can be simplified, the calculation amount of subsequent iris image identification can be greatly reduced, and the identification efficiency of the iris identification process is improved.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: provided are an efficient iris recognition method and device.
The solution of the invention for solving the technical problem is as follows:
an efficient iris recognition method comprises the following steps:
step 100, collecting a plurality of human eye images, and defining the collected human eye images as initial images;
step 200, judging whether the initial image meets the identification requirement, and deleting the initial image which does not meet the identification requirement;
step 300, performing image preprocessing operation on the initial image;
step 400, obtaining an iris area in each initial image, and segmenting the iris area from the initial images to obtain a plurality of images to be detected;
and 500, identifying and matching the plurality of images to be detected with prestored iris images stored in a database.
As a further improvement of the above technical solution, step 200 includes the following steps:
step 210, judging whether the definition of each initial image meets the requirement, and deleting the initial images with insufficient definition;
step 220, judging whether each initial image has an iris area, and deleting the initial images without the iris area and the initial images with insufficient iris area.
As a further improvement of the above technical solution, step 210 includes the following steps:
step 211, performing image graying processing on the initial image;
step 212, performing image segmentation operation on the initial image by using a watershed algorithm to obtain a plurality of inspection areas;
step 213, calculating the area of each inspection area;
step 214, setting an area threshold and a quantity threshold, counting the quantity of the inspection regions smaller than the area threshold according to the area size of each inspection region, and if the quantity is larger than the quantity threshold, determining that the definition of the initial image is insufficient;
in step 215, the original image with insufficient sharpness is deleted.
As a further improvement of the above technical solution, step 220 includes the following steps:
step 221, performing gaussian filtering processing on the initial image;
step 222, performing image graying processing on the initial image;
step 223, performing edge detection on the initial image, calculating the gradient of the initial image, and determining the circumferential line of the iris area in the initial image;
step 224, drawing all gradient straight lines in the initial image in a two-dimensional Hough space;
step 225, identifying the point with the maximum intersection frequency of each gradient straight line, and taking the point as the center of a circle of an iris area in the initial image;
step 226, calculating the distance from the circle center to the circumference, and taking the distance as the radius of the iris area in the initial image;
step 227, setting a standard threshold, judging whether the radius of the iris area in the initial image is smaller than the standard threshold, and if so, deleting the initial image.
The invention also discloses an iris recognition device, which comprises:
the acquisition module is used for acquiring a plurality of human eye images and defining the acquired human eye images as initial images;
the image deleting module is used for judging whether the initial image meets the identification requirement or not and deleting the initial image which does not meet the identification requirement;
the preprocessing module is used for carrying out image preprocessing operation on the initial image;
the segmentation module is used for acquiring the iris area in each initial image and segmenting the iris area from the initial image to obtain a plurality of images to be detected;
and the matching module is used for identifying and matching the plurality of images to be detected with prestored iris images stored in the database.
As a further improvement of the above technical solution, the image deleting module includes:
the first deleting unit is used for judging whether the definition of each initial image meets the requirement or not and deleting the initial images with insufficient definition;
and the second deleting unit is used for judging whether the iris area exists in each initial image or not and deleting the initial image without the iris area and the initial image with the insufficient iris area.
As a further improvement of the above technical solution, the first deleting unit includes:
the first gray processing unit is used for carrying out image graying processing on the initial image;
the image segmentation unit is used for carrying out image segmentation operation on the initial image by utilizing a watershed algorithm to obtain a plurality of inspection areas;
the area calculation unit is used for calculating the area of each inspection area;
a first input unit for setting an area threshold value and a number threshold value;
the statistical unit is used for counting the number of the inspection regions smaller than the area threshold value according to the area size of each inspection region;
the first judging unit is used for judging whether the initial image meets the definition requirement according to the number of the detection areas in the initial image, wherein the area of the detection areas is smaller than the area threshold, and if the number is larger than the number threshold, the definition of the initial image is determined to be insufficient;
and the first clearing unit is used for deleting the initial image with insufficient definition.
As a further improvement of the above technical solution, the second deleting unit includes:
the filtering unit is used for carrying out Gaussian filtering processing on the initial image;
the second gray processing unit is used for carrying out image gray processing on the initial image;
a circumference line determining unit, configured to perform edge detection on the initial image, calculate a gradient of the initial image, and determine a circumference line of an iris region in the initial image;
the system comprises a drawing unit, a calculating unit and a calculating unit, wherein the drawing unit is used for drawing all gradient straight lines in an initial image in a two-dimensional Hough space;
the circle center identification unit is used for identifying the point with the maximum intersection frequency of the gradient straight lines, and taking the point as the circle center of the iris area in the initial image;
the radius calculation unit is used for calculating the distance from the circle center to the circumference line, and taking the distance as the radius of the iris area in the initial image;
a second input unit for setting a standard threshold;
the second judging unit is used for judging whether the radius of the iris area in the initial image is smaller than a standard threshold value or not;
and the second clearing unit is used for deleting the initial image with the iris area radius smaller than the standard threshold.
The invention has the beneficial effects that: before iris extraction and identification matching are carried out on the initial image, a deleting step is introduced, and the initial image which does not meet the identification requirement is deleted, so that the calculation amount caused by subsequent identification matching on the initial image is greatly reduced, and the identification efficiency of the iris identification process is improved.
Drawings
In order to more clearly illustrate the technical solution in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is clear that the described figures are only some embodiments of the invention, not all embodiments, and that a person skilled in the art can also derive other designs and figures from them without inventive effort.
Fig. 1 is a flow chart of the identification method of the present invention.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the features and the effects of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all embodiments, and other embodiments obtained by those skilled in the art without inventive efforts based on the embodiments of the present application belong to the protection scope of the present application.
Referring to fig. 1, the present application discloses an efficient iris recognition method, a first embodiment of which includes the steps of:
step 100, collecting a plurality of human eye images, and defining the collected human eye images as initial images;
step 200, judging whether the initial image meets the identification requirement, and deleting the initial image which does not meet the identification requirement;
step 300, performing image preprocessing operation on the initial image, thereby providing the image quality of the initial image and the accuracy of image matching identification in subsequent operation;
step 400, obtaining an iris area in each initial image, and segmenting the iris area from the initial images to obtain a plurality of images to be detected;
and 500, identifying and matching the plurality of images to be detected with prestored iris images stored in a database.
Specifically, compared with the prior art, the embodiment is mainly distinguished in that a deletion step is introduced, and the initial image which does not meet the identification requirement is deleted, so that the subsequent identification and matching of the initial image is greatly reduced, the calculation amount is reduced, and the identification efficiency of the iris identification process is improved.
Further as a preferred implementation manner, the identification requirement in step 200 of this embodiment includes that the initial image is required to simultaneously satisfy two requirements of sufficient definition and a sufficiently large iris area, and it is considered that, in practical application, in the process of acquiring an image of a human eye, a target person may be far away from a human eye acquisition instrument or a body may shake, so as to affect the image acquisition quality. Step 200 in this embodiment includes the following steps:
step 210, judging whether the definition of each initial image meets the requirement, and deleting the initial images with insufficient definition;
step 220, judging whether each initial image has an iris area, and deleting the initial images without the iris area and the initial images with insufficient iris area.
Further as a preferred implementation manner, step 210 in this embodiment includes the following steps:
step 211, performing image graying processing on the initial image;
step 212, performing image segmentation operation on the initial image by using a watershed algorithm to obtain a plurality of inspection areas;
step 213, calculating the area of each inspection area;
step 214, setting an area threshold and a quantity threshold, counting the quantity of the inspection regions smaller than the area threshold according to the area size of each inspection region, and if the quantity is larger than the quantity threshold, determining that the definition of the initial image is insufficient;
in step 215, the original image with insufficient sharpness is deleted.
Specifically, the embodiment specifically implements a definition calculation function based on a watershed algorithm, the initial image is segmented into a plurality of inspection regions by using the watershed algorithm, and for an image with blurriness and lower definition, the inspection regions with smaller areas obtained after segmentation are more, that is, the number of the inspection regions with areas lower than an area threshold is used as a basis for judging the definition of the initial image, so that the judgment accuracy is high, the computation amount is low, and the computation efficiency of the entire iris identification process is not affected.
Of course, in order to further improve the operation efficiency of the iris identification process, step 210 in this embodiment further includes step 215, arranging each of the initial images according to the sharpness of the initial image, and retaining a plurality of initial images with the highest sharpness.
Further as a preferred implementation manner, step 220 in this embodiment includes the following steps:
step 221, performing gaussian filtering processing on the initial image;
step 222, performing image graying processing on the initial image;
step 223, performing edge detection on the initial image, calculating the gradient of the initial image, and determining the circumferential line of the iris area in the initial image;
step 224, drawing all gradient straight lines in the initial image in a two-dimensional Hough space;
step 225, identifying the point with the maximum intersection frequency of each gradient straight line, and taking the point as the center of a circle of an iris area in the initial image;
step 226, calculating the distance from the circle center to the circumference, and taking the distance as the radius of the iris area in the initial image;
step 227, setting a standard threshold, judging whether the radius of the iris area in the initial image is smaller than the standard threshold, and if so, deleting the initial image.
The application also discloses an iris recognition device simultaneously, and its first embodiment includes:
the acquisition module is used for acquiring a plurality of human eye images and defining the acquired human eye images as initial images;
the image deleting module is used for judging whether the initial image meets the identification requirement or not and deleting the initial image which does not meet the identification requirement;
the preprocessing module is used for carrying out image preprocessing operation on the initial image;
the segmentation module is used for acquiring the iris area in each initial image and segmenting the iris area from the initial image to obtain a plurality of images to be detected;
and the matching module is used for identifying and matching the plurality of images to be detected with prestored iris images stored in the database.
Further preferably, in this embodiment, the image deleting module includes:
the first deleting unit is used for judging whether the definition of each initial image meets the requirement or not and deleting the initial images with insufficient definition;
and the second deleting unit is used for judging whether the iris area exists in each initial image or not and deleting the initial image without the iris area and the initial image with the insufficient iris area.
Further preferably, in this embodiment, the first deleting unit includes:
the first gray processing unit is used for carrying out image graying processing on the initial image;
the image segmentation unit is used for carrying out image segmentation operation on the initial image by utilizing a watershed algorithm to obtain a plurality of inspection areas;
the area calculation unit is used for calculating the area of each inspection area;
a first input unit for setting an area threshold value and a number threshold value;
the statistical unit is used for counting the number of the inspection regions smaller than the area threshold value according to the area size of each inspection region;
the first judging unit is used for judging whether the initial image meets the definition requirement according to the number of the detection areas in the initial image, wherein the area of the detection areas is smaller than the area threshold, and if the number is larger than the number threshold, the definition of the initial image is determined to be insufficient;
and the first clearing unit is used for deleting the initial image with insufficient definition.
Of course, in order to further improve the operation efficiency of the iris identification process, in this embodiment, the first deleting unit further includes a sorting unit, configured to sort each initial image according to the definition of the initial image, and retain a plurality of initial images with the highest definition.
Further preferably, in this embodiment, the second deleting unit includes:
the filtering unit is used for carrying out Gaussian filtering processing on the initial image;
the second gray processing unit is used for carrying out image gray processing on the initial image;
a circumference line determining unit, configured to perform edge detection on the initial image, calculate a gradient of the initial image, and determine a circumference line of an iris region in the initial image;
the system comprises a drawing unit, a calculating unit and a calculating unit, wherein the drawing unit is used for drawing all gradient straight lines in an initial image in a two-dimensional Hough space;
the circle center identification unit is used for identifying the point with the maximum intersection frequency of the gradient straight lines, and taking the point as the circle center of the iris area in the initial image;
the radius calculation unit is used for calculating the distance from the circle center to the circumference line, and taking the distance as the radius of the iris area in the initial image;
a second input unit for setting a standard threshold;
the second judging unit is used for judging whether the radius of the iris area in the initial image is smaller than a standard threshold value or not;
and the second clearing unit is used for deleting the initial image with the iris area radius smaller than the standard threshold.
While the preferred embodiments of the present invention have been described in detail, it should be understood that the invention is not limited to those precise embodiments, and that various changes and modifications may be effected therein by one skilled in the art without departing from the scope or spirit of the invention as defined in the appended claims.
Claims (8)
1. An efficient iris identification method is characterized by comprising the following steps:
step 100, collecting a plurality of human eye images, and defining the collected human eye images as initial images;
step 200, judging whether the initial image meets the identification requirement, and deleting the initial image which does not meet the identification requirement;
step 300, performing image preprocessing operation on the initial image;
step 400, obtaining an iris area in each initial image, and segmenting the iris area from the initial images to obtain a plurality of images to be detected;
and 500, identifying and matching the plurality of images to be detected with prestored iris images stored in a database.
2. An efficient iris identification method according to claim 1, wherein the step 200 comprises the steps of:
step 210, judging whether the definition of each initial image meets the requirement, and deleting the initial images with insufficient definition;
step 220, judging whether each initial image has an iris area, and deleting the initial images without the iris area and the initial images with insufficient iris area.
3. An efficient iris recognition method as claimed in claim 2, wherein: step 210 includes the steps of:
step 211, performing image graying processing on the initial image;
step 212, performing image segmentation operation on the initial image by using a watershed algorithm to obtain a plurality of inspection areas;
step 213, calculating the area of each inspection area;
step 214, setting an area threshold and a quantity threshold, counting the quantity of the inspection regions smaller than the area threshold according to the area size of each inspection region, and if the quantity is larger than the quantity threshold, determining that the definition of the initial image is insufficient;
in step 215, the original image with insufficient sharpness is deleted.
4. An efficient iris recognition method as claimed in claim 2, wherein: step 220 includes the following steps:
step 221, performing gaussian filtering processing on the initial image;
step 222, performing image graying processing on the initial image;
step 223, performing edge detection on the initial image, calculating the gradient of the initial image, and determining the circumferential line of the iris area in the initial image;
step 224, drawing all gradient straight lines in the initial image in a two-dimensional Hough space;
step 225, identifying the point with the maximum intersection frequency of each gradient straight line, and taking the point as the center of a circle of an iris area in the initial image;
step 226, calculating the distance from the circle center to the circumference, and taking the distance as the radius of the iris area in the initial image;
step 227, setting a standard threshold, judging whether the radius of the iris area in the initial image is smaller than the standard threshold, and if so, deleting the initial image.
5. An iris recognition apparatus, comprising:
the acquisition module is used for acquiring a plurality of human eye images and defining the acquired human eye images as initial images;
the image deleting module is used for judging whether the initial image meets the identification requirement or not and deleting the initial image which does not meet the identification requirement;
the preprocessing module is used for carrying out image preprocessing operation on the initial image;
the segmentation module is used for acquiring the iris area in each initial image and segmenting the iris area from the initial image to obtain a plurality of images to be detected;
and the matching module is used for identifying and matching the plurality of images to be detected with prestored iris images stored in the database.
6. An iris identification device of claim 5, wherein the image deleting module comprises:
the first deleting unit is used for judging whether the definition of each initial image meets the requirement or not and deleting the initial images with insufficient definition;
and the second deleting unit is used for judging whether the iris area exists in each initial image or not and deleting the initial image without the iris area and the initial image with the insufficient iris area.
7. An iris identification apparatus as claimed in claim 6, wherein the first deleting unit comprises:
the first gray processing unit is used for carrying out image graying processing on the initial image;
the image segmentation unit is used for carrying out image segmentation operation on the initial image by utilizing a watershed algorithm to obtain a plurality of inspection areas;
the area calculation unit is used for calculating the area of each inspection area;
a first input unit for setting an area threshold value and a number threshold value;
the statistical unit is used for counting the number of the inspection regions smaller than the area threshold value according to the area size of each inspection region;
the first judging unit is used for judging whether the initial image meets the definition requirement according to the number of the detection areas in the initial image, wherein the area of the detection areas is smaller than the area threshold, and if the number is larger than the number threshold, the definition of the initial image is determined to be insufficient;
and the first clearing unit is used for deleting the initial image with insufficient definition.
8. An iris identification apparatus as claimed in claim 6, wherein the second deleting unit comprises:
the filtering unit is used for carrying out Gaussian filtering processing on the initial image;
the second gray processing unit is used for carrying out image gray processing on the initial image;
a circumference line determining unit, configured to perform edge detection on the initial image, calculate a gradient of the initial image, and determine a circumference line of an iris region in the initial image;
the system comprises a drawing unit, a calculating unit and a calculating unit, wherein the drawing unit is used for drawing all gradient straight lines in an initial image in a two-dimensional Hough space;
the circle center identification unit is used for identifying the point with the maximum intersection frequency of the gradient straight lines, and taking the point as the circle center of the iris area in the initial image;
the radius calculation unit is used for calculating the distance from the circle center to the circumference line, and taking the distance as the radius of the iris area in the initial image;
a second input unit for setting a standard threshold;
the second judging unit is used for judging whether the radius of the iris area in the initial image is smaller than a standard threshold value or not;
and the second clearing unit is used for deleting the initial image with the iris area radius smaller than the standard threshold.
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