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Alternative TitleA Study on Contactless Palmprint Recognition
Thesis Advisor刘昌平 ; 黄磊
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword掌纹识别 手掌检测 生物特征识别 Palmprint Recognition Hand Detection Biometrics
Abstract随着网络与信息技术的飞速发展,信息安全显得越发的重要,越来越多的场合需要对信息访问者进行身份验证和识别。生物特征识别技术通过获取和识别人身体和行为上的个性特征作为个体身份判别的依据,从而提供了一种新颖有效的信息安全解决方案。掌纹识别是生物特征识别技术中的一个新兴成员。它通过比较手掌掌心内侧区域的纹线结构判断人们的身份。近十年来,学术界在掌纹识别研究中所获得的识别率越来越高,掌纹图像的获取也越来越便捷,使得掌纹识别技术从理论研究逐步走向实际应用。 本文围绕非接触式掌纹图像的获取方式,预处理方法及掌纹纹线描述和识别的问题进行了深入地探讨,开展了下述研究工作: (1) 提出了非接触式掌纹识别的总体流程框架。在这个框架下,首先探讨了非接触式掌纹图像采集方式,设计了一种基于软约束条件的方案。该方案既满足了用户使用的便利性,又达到了掌纹识别对图像清晰度的要求。 (2) 设计了在开放条件下进行非接触式掌纹图像的手掌检测和识别区域定位方案。提出了基于手掌肤色和轮廓形状相结合的手掌检测方法,首先在复杂背景条件下,自动检测可用于识别的手掌图像,然后利用手掌主线信息对手掌的旋转,平移以及尺度变化进行自动校正和归一化,从而获得稳定的识别区域进行特征提取。 (3) 在非接触采集方式下,由于手掌姿态的变化,使得掌纹纹理发生拉伸,扭曲等非线性形变,降低了局部纹理描述的稳定性和识别性能。针对这一问题,我们提出基于对比度上下文的统计编码方法,描述掌纹的纹线特征。该方法一方面可以有效的表达纹线交叉的情况,另一方面在匹配时有效的去除了不稳定区域的干扰,对比实验获得了比竞争编码的方法更好的识别性能。
Other AbstractWith the development of information technology and computer networks, the information security becomes more and more important. In many situations, we need to verify personal identities before accessing private information. Biometrics emerges to provide a novel and effective solution to this demand. It captures and recognizes characteristics of human bodies or behaviors in order to achieve personal identification. Palmprint image recognition is a novel member in biometrics. It evaluates similarity of line-like textures inside central regions of palms between different individuals to recognize identities. In recent ten years, based on much research progress, the performance of palmprint recognition systems has been enhanced to a large degree. In this dissertation, we focus on the challenge of contactless palmprint recognition and investigate the problem of image acquisition, preprocessing, palmprint image representation and recognition. The main contributions of this thesis include: (1) We propose an overall framework of contactless palmprint recognition. Following this framework, we firstly investigate the problem of palmprint acquisition in a contactless way under complex backgrounds, through which we can get clear hand images. (2) We design prototype systems to achieve contactless palmprint image under cluttered scenes. In the systems, we combine characteristics of skin color and shape of hands to achieve automatic and efficient hand detection in complex scenes. Based on results of hand detection, we correct and normalize rotation, translation and scales of subjects’ hands by the hand principal lines then obtain regions of interests for real-time palmprint recognition. (3) To describe the palmprint more accurately, we propose a palmprint representation based on contrast context histogram. This method can describe the palmprint more clearly and remove the unsteady point when matching the palmprint. So the result of this representation is much better than the competitive code method.
Other Identifier200928014628034
Document Type学位论文
Recommended Citation
GB/T 7714
冯毅. 非接触掌纹识别研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2012.
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