一种用于虹膜图像分割的圆形边缘检测方法

Shashidhara H R, A. Aswath
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引用次数: 11

摘要

本文详细介绍了虹膜区域分割作为虹膜识别的一种生物特征个人识别与验证方法。人的虹膜是独一无二的,因人而异。就像指纹一样,生物医学证明人类的虹膜是独特的。此外,虹膜可以很容易地从任何视觉捕捉设备访问。虹膜的二维结构进一步辅助了这项技术。本文描述了人眼图像中虹膜区域的提取方法。提出了一种从图像中分割虹膜的新方法。它是一种新的圆形边缘检测技术,尤其适用于虹膜识别。图像经过各种操作,如黑白转换、边缘检测和滤波。虹膜的强度介于瞳孔和眼睛其他部分的强度之间,这是提取虹膜的关键。在图像上进行简单的垂直和水平扫描以获得圆的切线。对图像进行数学分析,得到半径和圆心,从而绘制出虹膜的内外圆,或者利用得到的值进行霍夫变换,以获得更高的精度。我们在得到这些值后构造圆。
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A Novel Approach to Circular Edge Detection for Iris Image Segmentation
This paper details about segmentation of iris region for iris recognition as a biometrical personal identification and verification. Human iris is unique and differs from one individual to another. Just as finger prints, biomedical proves human irises are distinct. Also, iris can be easily accessed from any visual capturing device. The two dimensional structure of iris further assists the technology. This paper describes the extraction of iris region from an image of the human eye. The proposed algorithm defines a new method to segment Iris from the image. It's a new technique for circular edge detection particularly for Iris recognition. An image undergoes various operations like black and white conversion, edge detection and filtering. The fact that the intensity of iris lies between the intensities of pupil and rest of the eye is the key here to extract iris. A simple vertical and horizontal scan is done over the image to get the tangents of the circles. A mathematical analysis is done on the images to get the radius and the center of the circle and hence the inner and outer circles of the iris are drawn or Hough transform can be done using the obtained values for more accuracy. We are constructed the circles after obtaining the values.
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