【作者】 王玉茹；

【导师】 吕英华； 孔俊；

【作者基本信息】 东北师范大学 ， 计算机应用技术， 2006， 硕士

【摘要】 近年来,生物识别技术作为身份识别的手段越来越受到人们的重视。生物识别技术是指基于已知的生物特征图像库,利用图像处理和模式识别技术,从场景中识别和验证身份,是一种以生物技术为基础,以信息技术为手段,将生物和信息这两种技术融合为一体的模式识别技术。作为生物识别领域新兴的生物特征,掌纹以其所具有的唯一性,一定时期的稳定性、信息量大以及采集方便等优点,得到了国内外许多研究者的重视。掌纹识别技术的深入研究,不仅能带来安全认证、监控与管理以及模式识别等理论的重大发展,而且也将产生重大的社会与经济效应。本文对掌纹识别领域内现存方法的缺点和问题进行了分析,在图像采集,预处理,特征提取和匹配几个方面进行了改进和创新。提出了一种具有自适应性和鲁棒性的手纹识别算法,充分利用了手的两种特征——掌纹和手指纹线。系统包括两部分:一个方便的手纹图像获取设备和快速可靠的手纹识别算法。为了准确有效地进行特征提取,定义了一个鲁棒而自适应的图像坐标系统,并应用了小波零交叉和二维Gabor滤波器对掌纹图像进行多特征编码。在识别阶段采用了由粗到细的匹配策略。在粗级别分类应用手指纹线信号的一维小波零交叉编码,细级别匹配采用掌纹的一维小波零交叉编码和二维Gabor滤波器编码作为掌纹特征。本文通过这种编码技术和逐级匹配策略实现了一个基于手纹的身份识别系统,并进行了大量的实验,实验结果证实了系统的有效性和可靠性。更多还原

【Abstract】 Biometric personal identification is emerging as a powerful means for automaticallyrecognizing a person’s identity, and is attracting much attention lately. The biometriccomputing-based approach is concerned with identifying a person based on a knownbiometric feature database by image processing and pattern recognition technology, and it is akind of pattern recognition which applies biometric and informatics technology, taking thebiometric technology as basement and information as means. As a new biometric feature,palm-print has received much attention from researchers, because it has the advantages ofuniqueness, stability, containing more information and easily captured. Above all, the furtherresearch of palm-print identification technology can bring with not only the greatdevelopment of authentication, control and management theory, but also the benefit to societyand economy.Combined with the previous work of other researchers, a discussion is elaborately madeon the key techniques concerning image capturing, pre-processing, feature extraction andmatching and some improved and creative approaches to these problems are put forward. Anadaptive and robust verification technology by making use of hand-print features is proposed.Two hand-based features, the finger-print and the palm-print are considered. In contrast to theexisting approaches, our system employs both 1D and 2D hand-print signal to achieveeffective personal identification. The system consists of two parts: a convenient device forhand-print image acquisition and an efficient algorithm for fast palm-print recognition. Arobust and adaptive image coordinate system is defined to facilitate feature extraction. And adiscrete wavelet zero-crossing and 2D Gabor encoding scheme is applied to hand-printmulti-feature extraction and representation. In addition, a dynamic selection scheme isproposed to facilitate the fast search for the best matching of the sample in database in ahierarchical fashion. Particularly, wavelet zero-crossing coded 1D finger-print feature isapplied in the coarse level classification, and both 1D wavelet zero-crossing and 2D Gaborfeature are provided for the fine level matching. Based on the coding scheme and hierarchicalmatching strategy, this paper implements a hand-based personal identification system, andexperimental results demonstrate the effectiveness of the proposed system.更多还原