Human iris identifying method

Abstract

A method for identifying iris of human eye includes detecting four boundary points of pupil and accurately positioning pupil centre, detecting four outer boundary point of its and confirming iris centre, expanding eye image in 360 degree around iris center to be rectangle for searching pupil boundary, carrying out topological conversion to realize iris image noralization.

Description

technical field [0001] The invention belongs to the human eye iris recognition technology, in particular to the contents of iris segmentation, iris feature extraction, matching and recognition in the human eye recognition technology. Background technique [0002] Human iris recognition technology is mainly composed of several parts such as eye image acquisition, iris segmentation, iris normalization, iris feature extraction, matching and recognition. Iris segmentation is to determine the boundary between iris and pupil, iris and sclera in the acquired human eye image, so as to separately extract the image of iris part. The iris segmentation method can be mainly divided into the following four basic types: the first method is through the Hough transform method, the problem is that it is first necessary to select a threshold for edge detection, which will lead to the loss of key edge points, resulting in circle Or the detection of the arc fails; secondly, the amount of calcul...

AI Technical Summary

Problems solved by technology

The iris segmentation method can be mainly divided into the following four basic types: the first method is through the Hough transform method, the problem is that it is first necessary to select a threshold for edge detection, which will lead to the loss of key edge points, resulting in circle Or the detection of the arc fails; secondly, the amount of calculation is large, which is not suitable for the application

The second method is through Daugman's circular boundary detection operator method, its positioning speed is faster than the Hough transform method, but for the noise in the image of the iris region, such as the presence of light reflection, this method is not suitable for application

The third method is through the method of active contour line, which is characterized in that the positioning speed is further improved compared with the first two methods, but it is necessary to roughly estimate the position of the pupil first, which is not accurate enough

The fourth method is to directly obtain the iris boundary through the method of edge detection. The problem is that the selection of the threshold may cause some edge points to be lost.

[0005] (1) Daugman's recognition method has limitations in use, that is, when collecting eye images, the reflection light should fall in the pupil, and a certain distance should be kept between the eye and the collector, which has to require the cooperation of the user, and at the same time Not suitable for collection of human iris on the go

[0006] (2) The current iris segmentation is the process of directly detecting the inner and outer circle boundaries in the eye image. The typical two segmentation methods not only have a large computational complexity, but also their detection performance is greatly affected by the quality of edge detection. Even cause the segmentation to fail

[0007] (3) Some algorithms have higher requirements for image acquisition quality

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