【作者】 张仁彦；

【导师】 赵国良；

【作者基本信息】 哈尔滨工程大学 ， 控制理论与控制工程， 2006， 博士

【摘要】 在现代社会中，随着科技和经济的飞速发展，人们对身份识别技术的重视程度也进一步提高。传统的身份识别技术，如：密码等，由于防伪性比较差，已经不能适应现代社会对身份识别的要求。为了克服传统身份识别技术的缺点，人们提出用人体的生物特征进行身份识别，如：指纹、虹膜和语音等。其中，虹膜身份识别技术由于其可靠性高等优点，正成为生物特征识别技术领域中的研究热点。论文对虹膜身份识别算法进行了研究，主要工作有： 首先，研究了虹膜内边缘的定位算法，并提出两种虹膜内边缘定位方法。第一种方法，以虹膜图像灰度直方图为基础，通过寻找瞳孔区灰度分布范围的方法确定分离瞳孔的灰度阈值，并利用灰度投影法定位虹膜内边缘；第二种方法，对虹膜图像行列灰度曲线的几何特征进行了深入分析，并提出利用虹膜图像行列灰度曲线几何特征进行瞳孔定位的方法。这两种方法都取得了比较好的定位效果。 然后，为了设计出简单、可靠的图像边缘检测算法，为虹膜外边缘定位奠定基础，对以人眼视觉特性为基础的图像边缘检测技术进行了深入研究，并提出了多种以人眼视觉特性为基础的边缘检测方法，包括：灰度比值法、反色-灰度比值法、灰度差和比值法、反色-灰度差和比值法、灰度比例对数差值法、反色-灰度比例对数差值法、灰度整比例对数差值法、反色-灰度整比例对数差值法和灰度比例幂差值法。实验结果表明这些算法都能有效地检测图像边缘。 接着，对虹膜外边缘定位方法进行了研究，将灰度整比例对数差值法和反色-灰度整比例对数差值法用于虹膜外边缘检测，取得了比较高的定位准确率。 最后，以纹理分析、随机信号分析和Gabor变换为基础，并结合比较成功的虹膜特征提取算法—Gabor变换法，对虹膜纹理的特性进行了分析。以虹膜纹理特性分析的结果为基础，提出了瑞利分布型滤波器，并将其用于虹膜特征提取，取得了比较好的识别效果。 实验结果表明本文提出的算法能够有效地进行虹膜身份识别。更多还原

【Abstract】 In modern times, going with the development of science, technology and economy, people think much of identity recognition more and more. But traditional identity recognition technologies such as password etc. have not suit the identity recognition in modern times for their bad ability against forging. For overcoming the disadvantages of traditional identity recognition technologies, biometrics recognition methods were brought forward such as fingerprint, iris and voice. Among these biometrics recognition methods, the research on iris recognition has received increasing attention because of its high reliability, In this dissertation the iris recognition algorithm was researched, and the main works are as follows:Firstly, researched the location of the iris inner boundary, and put forward two iris inner boundary location methods. The first method fixed on the gray scale threshold for pupil’s segmentation by finding the pupil’s gray scale range, based on the gray scale histogram of the iris image, and located the pupil by gray scale projection. The second method researched deeply the characteristics of iris image’s row and column gray scale curves, and put forward locating the iris inner boundary by the characteristics. The two methods can all locate the iris inner boundary successfully.Secondly, the edge detection methods were researched based on human’s visual characteristics for designing simple and reliable edge detection method to locating the iris outer boundary. And put forward several edge detection methods based on human’s visual characteristics: the method of the gray scale ratio, the negative gray scale ratio, the gray scale difference-sum ratio, the negative gray scale difference-sum ratio, the gray scale proportion logarithm difference, the negative gray scale proportion logarithm difference, the gray scale integer proportion logarithm difference, the negative gray scale integer proportion logarithm difference and the gray scale proportion power difference. The test results show these methods can all detect image edges effectively.更多还原