【作者】 辛瑞宁；

【导师】 李昆仑；

【作者基本信息】 河北大学 ， 通信与信息系统， 2012， 硕士

【摘要】 随着社会的进步和经济的发展，法制观念逐步加深，对个人身份识别的需求越来越广泛。鉴于传统身份识别方法中存在的一些弊端，生物特征识别技术开始受到人们的广泛关注。指横纹特征是一种新兴的生物特征，除了具有与其他手部特征一样的稳定性和可区分性特点外，还有其独有的特征。本文选择指横纹特征进行身份识别，并对识别过程中的特征提取算法展开研究。在指横纹识别过程中，特征提取是一个关键的步骤，如何提取有效的特征就成为关注的重点问题之一。由于单一的生物特征进行身份识别有一定的局限性，信息融合被引入到指横纹识别中。本文对指横纹特征提取算法和特征级融合算法进行了深入的研究，主要工作如下：(1)对指横纹的特征提取进行了研究。利用经典的特征提取方法，分别使用Gabor滤波提取指横纹特征、PCA提取指横纹特征，并提出了用局部二进制模式(LBP)的方法提取指横纹特征的方法。(2)提出了基于Gabor与PCA相结合的指横纹特征提取的算法，首先对指横纹进行Gabor变换，然后使用PCA进行降维，最后根据欧氏距离对指横纹匹配识别。实验表明该方法得到的识别率要高于单独使用Gabor和PCA方法的结果。(3)鉴于单一特征进行身份识别具有局限性，本文提出了特征融合的方法。应用Gabor滤波器对指横纹图像进行滤波得到其特征，然后融合四个手指的特征，实现了指横纹识别。通过在北京交通大学指横纹数据库及实验室自行采集建立的图像库实验证明，本文算法可以有效地实现指横纹特征识别。更多还原

【Abstract】 With the rapid development of modern science and technology, the concept of legalsystem gradually deepens, the demand for personal identification is more and more extensive,because of the drawbacks of the traditional identification methods, biometric technology wasborn, and is now widely used in various fields. Knuckle-print is an emerging biometric; it hasspecial features in addition to other characteristics such as the stability and distinguishcharacteristics. In this paper, the Knuckle-print was chosen for Biometric identification, andstudy the feature extraction algorithm in the identification process.Feature extraction is the key to the whole process of the Knuckle-print recognition, howto extract features effectively is becoming one of the important attentions. Because of certainlimitations of single biological characteristics, information fusion is introduced to thebiological characteristics identification. This paper put forward feature extraction algorithmand character fusion algorithm, the main research work are as follows:(1)Feature extraction of the Knuckle-print. We use the typical method of featureextraction which is the Gabor filter, PCA to extract features respectively, and propose amethod which is based on the local binary mode to extract the Knuckle-print feature.(2) Put forward algorithm based on Gabor and PCA for the feature extraction of theKnuckle-print. The experimental results show that the recognition rate of the method is betterthan used Gabor and PCA method alone respectively.(3) This paper puts forward method of the characteristics fusion for the Knuckle-printrecognition due to the limitations of the single feature identification.The proposed algorithms can effectively implement knuckle-print identification. It isshown by experiments which proceed in our own building image data and the data providedby Information Institute of Beijing Jiaotong University.更多还原