A fast and accurate iris segmentation method using an LoG filter and its zero-crossings
Abstract
This paper presents a hybrid approach to achieve iris localization based on a Laplacian of Gaussian (LoG) filter, region growing, and zero-crossings of the LoG filter. In the proposed method, an LoG filter with region growing is used to detect the pupil region. Subsequently, zero-crossings of the LoG filter are used to accurately mark the inner and outer circular boundaries. The use of LoG based blob detection along with zero-crossings makes the inner and outer circle detection fast and robust. The proposed method has been tested on three public databases: MMU version 1.0, CASIA-IrisV1 and CASIA-IrisV3- Lamp. The experimental results demonstrate the segmentation accuracy of the proposed method. The robustness of the proposed method is also validated in the presence of noise, such as eyelashes, a reflection of the pupil, Poisson, Gaussian, speckle and salt-and-pepper noise. The comparison with well-known methods demonstrates the superior performance of the proposed method's accuracy and speed.
Cite
@article{arxiv.2201.06176,
title = {A fast and accurate iris segmentation method using an LoG filter and its zero-crossings},
author = {Tariq M. Khan and Donald G. bailey and Yinan Kong},
journal= {arXiv preprint arXiv:2201.06176},
year = {2022}
}