Iris Recognition: A Java based implementation

Kaushik Roy, Darrel Hudgin, Prabir Bhattacharya, Ramesh Chandra Debnath
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引用次数: 5

Abstract

Biometric authentication has become increasingly popular in security systems. Recently, the systems based on the human iris, which develops a unique pattern before birth, have produced very high rates of recognition. The iris image is first blurred using a Gaussian filter, and the edge is detected using the Canny edge detection technique. An algorithm, which uses the center of the image as a starting point, is proposed to isolate the pupillary region. The initial estimate of the location of the pupil is then refined, and the iris is located by using the integrodifferential operator. In order to detect the upper and the lower eyelids, we deploy the integrodifferential operator again; however, the path of contour integration is changed from circular to arcuate. A thresholding technique is then applied to locate the eyelashes. The annular iris region is unwrapped from a polar coordinate system to a rectangular canvas. The 2D Gabor wavelets are used to extract the discriminating features. Then, the phase information is extracted to produce an iris code of 2048 bit and a mask, which denotes the noisy regions, of the same length. The Hamming distance is applied for the matching purpose. We also design a graphical user interface (GUI) in Java which allows the comparison of two images, the verification that an image is that of a specific person, and to search through the previously scanned irises for an exact match. The proposed scheme is computationally effective as well as reliable in term of recognition rate of 99.21%.
虹膜识别:基于Java的实现
生物识别认证在安全系统中越来越受欢迎。最近,基于人类虹膜的系统产生了非常高的识别率,虹膜在出生前就形成了独特的模式。首先使用高斯滤波器模糊虹膜图像,然后使用Canny边缘检测技术检测边缘。提出了一种以图像中心为起始点的瞳孔区域隔离算法。然后对瞳孔位置的初始估计进行细化,利用积分微分算子对虹膜进行定位。为了检测上下眼睑,我们再次使用积分微分算子;然而,轮廓积分的路径由圆形变为弧形。然后应用阈值技术来定位睫毛。环形虹膜区域从极坐标系解包裹到矩形画布。利用二维Gabor小波提取识别特征。然后,提取相位信息,得到2048比特的虹膜编码和相同长度的表示噪声区域的掩码。汉明距离用于匹配目的。我们还用Java设计了一个图形用户界面(GUI),它允许比较两张图像,验证图像是否属于特定的人,并通过先前扫描的虹膜搜索精确匹配的虹膜。该方案具有良好的计算效率和可靠性,识别率达99.21%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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