A Simple Shape Prior Model for Iris Image SegmentationReportar como inadecuado

A Simple Shape Prior Model for Iris Image Segmentation

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In order to make biometric systems faster and more user-friendly, lower-quality images must be accepted. Amajor hurdle in this task is accurate segmentation of the boundaries of the iris in these images. Quite commonly,circle-fitting is used to approximate the boundaries of the inner pupil and outer limbic boundaries of the iris,but this assumption does not hold for off-axis or otherwise non-circular boundaries. In this paper we present anovel, foundational method for elliptical segmentation of off-axis iris images. This method uses active contourswith constrained flow to achieve a simplified form of shape prior active contours. This is done by calculating aregion-based contour evolution and projecting it upon a properly chosen set of vectors to confine it to a classof shapes. In this case, that class of shapes is ellipses. This serves to regularize the contour, simplifying thecurve evolution and preventing the development of irregularities that present challenges in iris segmentation.The proposed method is tested using images from the UBIRIS v.1 and CASIA-IrisV3 image data sets, withboth near-ideal and off-axis images. Additional testing has been performed using the WVU Off Axis-Angle IrisDataset, Release 1. By avoiding many of the assumptions commonly used in iris segmentation methods, theproposed method is able to accurately fit elliptical boundaries to off-axis images.

Laboratory of Computational Computer Vision Publications -

Autor: Bishop, Daniel A. - Yezzi, Anthony, Jr. - -

Fuente: https://smartech.gatech.edu/

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