Abstract
In any accurate iris recognition system segmentation of iris plays a vital role. The noise, specular reflections, eyelid/eyelash obstruction, and intensity inhomogeneities in an image make the segmentation more difficult. In this paper, a novel technique is proposed to segment the iris from images that are taken under uncooperative image conditions. The proposed method segments the image in two stages. Firstly, Morphological reconstruction fuzzy c-means clustering (MRFCM) based on an improved differential search algorithm is implemented before the segmentation step. The MRFCM can preserve image contours even in the presence of noise. Secondly, the iris is isolated from the undesired regions of an eye image by implementing geodesic active contours driven by a modified stopping criterion on the resultant images of the pre-segmentation step. The accuracy of the method presented has been tested on the databases such as CASIAv3-Interval, UBIRISv1, MMU1, IITDv1, and MICHE-I. The segmentation accuracy has been demonstrated and compared with other existing methods present in the literature. The obtained results are promising and the proposed model is outperformed the existing methods.
Highlights
The individual identification based on the iris is one of the most important biometrics due to its unique and apparently stable iris patterns
The proposed technique is tested on the MICHE-I database, which was used in the competition named Mobile Iris Challenge Evaluation-I (MICHE-I)
Images in the UBIRISv1 and MICHE-I databases are collected under visible wavelength (VW) and uncooperative scenario
Summary
The individual identification based on the iris is one of the most important biometrics due to its unique and apparently stable iris patterns. The noise artifacts such as eyelashes/eyelids occlusion, specular reflections, blurring, non-circular iris boundaries, off-axis gaze, etc., make the segmentation more difficult. Segmentation of perfect (ideal) iris images and segmentation of degraded (non-ideal) iris images. For the segmentation of ideal iris images, numerous techniques have been suggested by many researchers in the literature [1,2,3,4,5,6,7,8,9]. Segmentation of degraded iris images has grabbed attention for a decade
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