Abstract
In view of the problem of unstable recognition effect and low robustness of a traditional iris location algorithm, an iris location algorithm based on union‐find‐set and block search is proposed. Firstly, the inner circle of the iris is roughly positioned by the method of retrieval, and then, the Hough transform is used to accurately locate the pupil. After that, the convolution operation is used to roughly locate the outer circle, and then, the original image is partitioned to search. And the grayscale change in the gray histogram of the screenshot is observed to accurately locate the outer circle. The obtained iris and the iris obtained by the traditional localization algorithm are processed by the same iris recognition algorithm. The results show that the proposed image is more effective in image recognition and has good robustness.
Highlights
Due to the uniqueness, noninvasiveness, stability, and natural anticounterfeiting of the iris, the iris has higher accuracy than other biometrics [1]
The iris recognition process is divided into iris image acquisition, iris quality evaluation, iris location, iris normalization enhancement, and iris feature expression and matching [2]
The inner boundary of the iris is roughly located by using the lower edge of the binary image, and the outer boundary of the iris is roughly located by using the one-dimensional gray mean signal on both sides of the inner boundary center [6]
Summary
Noninvasiveness, stability, and natural anticounterfeiting of the iris, the iris has higher accuracy than other biometrics [1]. Traditional iris location algorithms include the calculus circle template method and Hough method based on edge detection [4, 5]. An iris location algorithm based on edge detection and circle fitting is proposed [7]. The iris location algorithm based on a smallscale search is adopted [8]. These algorithms can accurately locate the position of the iris, they have poor robustness and high requirements for the image. They have poor anti-interference ability to rough eyelids, illumination, and other noise interference, and the recognition effect is unstable. Localization, and the iris images acquired by different collectors under different conditions can be used for iris localization, and the recognition effect is stable
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