【作者】 徐昶；

【导师】 印勇；

【作者基本信息】 重庆大学 ， 信号与信息处理， 2005， 硕士

【摘要】 随着信息技术的发展和日益增长的对安全的需要,基于生物特征的身份识别技术在近年来有了迅速的发展。作为生物特征识别技术之一的虹膜识别技术正在兴起,并显示了很大的优越性。在现有各类生物识别技术中,虹膜识别是相对较新并且具有巨大潜力的技术。虹膜识别技术具有以下特点:虹膜图像的采集具有无侵犯性;瞳孔的缩放使虹膜组织具有活体组织的显著特征,可以有效的防止人工伪造等等。虹膜识别系统主要包括了图像采集、虹膜定位、虹膜识别和模式匹配四个部分。它的研究主要涉及到了计算机视觉、数字图像处理、小波理论、模式识别等众多学科领域。其中定位和识别是该系统最为关键的部分。本文首先介绍了虹膜识别技术的诞生、发展以及研究现状,对虹膜识别系统和现有的几种虹膜识别算法进行了系统的研究和讨论。然后分析了前人的一些定位算法,指出算法的不足,又结合数学形态学和轮廓跟踪等理论提出了新的虹膜定位方法。在虹膜特征提取算法中,研究了Daugman对虹膜纹理的编码方法,在识别算法中采用了Daugman提出的2-D Gabor小波。研究发现虹膜局部纹理的能量集中在一个频率上,根据这一特点对虹膜图像进行分块。提出了计算每个分块和Gabor小波互能谱的编码方法。经实验证明本文的定位算法速度较快,识别算法具有合理性和有效性。最后指出虹膜识别技术中仍然存在的问题以及该技术的发展前景。更多还原

【Abstract】 With the increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, a kind of biological characteristic recognition, springs up as a result of the social and economical development, and it shows great advantages. Iris recognition technology with its huge potential is relatively new among different kinds of biometric recognition technologies. For example, the characteristics of one’s iris are steady all one’s life, the capturing of iris image is non-invasive, and issues of iris possess the characters of living issues on account of the zooming process of pupils, which prevents counterfeiting. A typical iris recognition system includes iris imaging, iris location, iris recogntion and pattern matching. It involves numerous displine domains, such as computer vision and digital image processing, wavelet theory, pattern recognition etc. Iris location and recognition are the key of iris recognition system. In this paper we have introduced the birth, development and current situation of research on the iris recognition technique and studied the exisiting iris recognition algorithms. Then the algorithms on iris location are studied and the disadvantages are pointed. A new approach based on mathematic morphology and contours trace is put forward. After studing the means of Daugman’s encode of iris texture, we adopted 2-D Gabor wavelet that was advanced by Daugman to extract the feature. The iris image texture can be divided into many bands whose engegy centralize in one frequency. We put forward a new encoding method that calculates every band’s cross energy spectra with Gabor wavelets. The experiment results show that this location algorithm is faster and this encoding method is effective and reasonable. At the end of this thesis some existing problems are pointed out, then the good future of iris recognition technology is predicted.更多还原