Human Eye Pupil Detection System for Different IRIS Database Images

Q3 Chemistry
N. Nandhagopal, S. Navaneethan, V. Nivedita, A. Parimala, Dinesh Valluru
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引用次数: 10

Abstract

The pupil detection system plays a vital role in ophthalmology diagnosis equipments because pupil has a center place of human eye to locate the exact position. To identify the exact human eye pupil region in near infrared (NIR) images, this work proposes the Center of gravity method and its real time FPGA hardware implementation. The proposed work involves global threshold method to segment the pupil region from human eye and the bright spot suppression process removes the light reflections on the pupil due to the IR (Infra red) rays then the morphology dilation process removes unnecessary black pixels other than pupil region on the image. Finally, center of gravity (COG) method provides the exact pupil center coordinate and radius of the human eye. CASIA IRIS V4 and UBIRIS iris database images used in this work and achieved 90-95% of recognition rate.
不同IRIS数据库图像的人眼瞳孔检测系统
瞳孔检测系统在眼科诊断设备中起着至关重要的作用,因为瞳孔是人眼定位的中心位置。为了准确识别近红外图像中的人眼瞳孔区域,本文提出了重心法及其实时FPGA硬件实现。所提出的工作涉及全局阈值方法来分割人眼的瞳孔区域,亮点抑制过程去除了由于IR(红外)射线引起的瞳孔上的光反射,然后形态学膨胀过程去除了图像上瞳孔区域以外的不必要的黑像素。最后,重心(COG)方法提供了精确的人眼瞳孔中心坐标和半径。本工作使用CASIA IRIS V4和UBIRIS虹膜数据库图像,识别率达到90-95%。
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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来源期刊
Journal of Computational and Theoretical Nanoscience
Journal of Computational and Theoretical Nanoscience 工程技术-材料科学:综合
自引率
0.00%
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0
审稿时长
3.9 months
期刊介绍: Information not localized
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