Abstract
Iris localization is the most crucial part of the iris processing because its accuracy can directly affect the accuracy of biometric identification in subsequent steps. Yet, the quality of iris images may be sharply degraded due to interference from eyelashes and reflections during image acquisition, which can affect the localization accuracy adversely. To solve the problem, an iris localization algorithm based on effective area is proposed. First, YOLOv4 is used to crop the image to obtain the effective iris area, which is beneficial in improving the accuracy of subsequent localization. Furthermore, a method to remove reflective noise is proposed, which can effectively avoid the problem of noise interference in the process of inner boundary determination. Finally, aiming at the edge deviation caused by eyelashes, an outer boundary adjustment method is proposed. The experimental results show that the proposed method achieves good performance in the localization of iris images of both good quality and noise interference and outperforms other state-of-the-art methods.
Highlights
With the rapid development of information security, the role of biometric technology in military, banking, e-commerce, security, and other fields is becoming increasingly more prominent
E integrodifferential operator (IDO) [2, 3], proposed by Daugman, and edge detection combined with the circular Hough transform (CHT) [4], proposed by Wildes, are classic algorithms used in iris localization, which have made great contributions to the research of iris localization
The classic algorithms have certain shortcomings usually: IDO is based on the difference in grayscale of adjacent pixels, so it is extremely sensitive to noise; CHT is based on voting on edge points, and it is difficult to set a universal threshold when the image is marginalized based on gradient information
Summary
Received 7 May 2021; Revised 26 May 2021; Accepted 3 June 2021; Published 22 June 2021. Iris localization is the most crucial part of the iris processing because its accuracy can directly affect the accuracy of biometric identification in subsequent steps. The quality of iris images may be sharply degraded due to interference from eyelashes and reflections during image acquisition, which can affect the localization accuracy adversely. An iris localization algorithm based on effective area is proposed. YOLOv4 is used to crop the image to obtain the effective iris area, which is beneficial in improving the accuracy of subsequent localization. A method to remove reflective noise is proposed, which can effectively avoid the problem of noise interference in the process of inner boundary determination. E experimental results show that the proposed method achieves good performance in the localization of iris images of both good quality and noise interference and outperforms other state-of-the-art methods Aiming at the edge deviation caused by eyelashes, an outer boundary adjustment method is proposed. e experimental results show that the proposed method achieves good performance in the localization of iris images of both good quality and noise interference and outperforms other state-of-the-art methods
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