【作者】 贾伟；

【导师】 黄德双；

【作者基本信息】 中国科学技术大学 ， 模式识别与智能系统， 2008， 博士

【摘要】 网络信息化社会中,许多场合需要对人的真实身份进行有效鉴别。生物特征识别技术是解决此问题的最为有效的途径。所谓生物特征识别技术就是指利用人体本身所固有的物理特征或者行为特征,通过图像处理、模式识别等方法来鉴别个人身份的技术。正由于生物特征识别技术的重要性以及广阔的市场前景,它越来越受到研究者们的重视,已经成为模式识别领域一个新的研究热点。掌纹识别是最近几年才发展起来的新的生物特征识别技术。相比指纹以及虹膜识别技术,掌纹识别有其独有的特点,如含有丰富的线、纹理和方向特征;低分辨率成像,采集设备成本不高;掌纹ROI区域定位容易;易于和手形、手掌静脉等特征组成多模态识别系统。更重要的是,掌纹识别也是一种识别精度很高的生物特征识别技术。因此,对掌纹识别技术进行深入研究是非常必要和迫切的。然而,掌纹识别技术尚处于发展阶段,其理论和应用方面的研究都有待于进一步深化和完善。在此背景下,本文对掌纹识别中的一些关键问题进行深入研究,在基于主线的识别、基于方向特征的识别、基于表征的识别、掌纹的快速检索以及多模态识别等几个方面提出了有效的算法。本文的主要工作概括如下:(1)掌线是掌纹的基本特征,本文提出一种基于主线特征的掌纹识别算法。在掌纹识别领域,首次利用主线进行掌纹识别,并且证明了主线特征也具有较好的辨别能力。在该方法中,提出一种改进的有限Radon变换,能够从复杂的掌纹图像中有效提取掌线的能量和方向特征,并能根据这两个特征准确提取掌纹主线。同时创新性的提出一种新的线匹配算法,该算法能克服小的旋转与位移给匹配造成的不利影响,具有很强的鲁棒性。(2)基于方向特征的方法是掌纹识别中性能最好的方法之一。本文提出一种基于方向特征的鲁棒掌纹验证算法。该方法在特征提取阶段,使用改进的有限Radon变换来提取掌纹的方向特征;在匹配阶段使用构造虚拟样本的方法来补偿旋转造成的匹配误差;同时提出点对区域的匹配方法,具有很强的容错性。实验结果表明,在掌纹识别领域,该方法是特征提取速度最快、等错率最低的算法之一。(3)提出一种基于掌纹方向表达的快速鲁棒掌纹识别算法。该方法首先使用两种策略来提高基于表征方法(Appearance based approaches)的识别性能。一是在掌纹识别领域,首次提出一种新的掌纹表达方式以应用于基于表征的方法,即掌纹的方向表达,相比于掌纹的原始表达,方向表达保持了掌纹结构特征同时,具有更强的辨别能力,同时对光照变化是鲁棒的;二是使用扩大训练集方法来补偿旋转和位移造成的类内匹配误差。在这两个策略下,基于表征方法的识别率有了显著提高。另一方面,为了增加掌纹识别的鲁棒性,提出一种融合方法,即融合基于方向表达的表征方法和基于方向特征的识别方法,该方法在香港理工大学的掌纹数据库上所做的实验获得了100%的正确识别率,以及非常低的等错率。在此基础上,在掌纹识别领域首次提出一种可实际应用的掌纹快速检索方法,即使用基于方向表达的表征方法进行检索构造数据库子集,然后使用融合方法进行最后分类识别。实验结果表明该检索方法比基于比特匹配的CompetitiveCode等方法快了约4倍。(4)提出一种分层的快速掌纹识别方法。在粗匹配阶段,提出一种新的掌纹快速检索方法,即使用掌纹主线进行检索。在检索的时候,使用少数的主线关键点进行匹配,提高了检索的速度。同时,在精细识别阶段,提出一种融合算法,即融合Tensor Marginal Fisher Analysis、Competitive Code和Phase-OnlyCorrelation方法,并把掌纹的方向表达和扩大训练集应用到Tensor MarginalFisher Analysis和Phase-Only Correlation方法中,最终获得了非常理想的识别结果。(5)提出一种新的基于脚纹识别的婴幼儿生物特征识别技术。首先设计了一个基于数码相机的脚纹采集设备,然后根据脚掌的轮廓信息来提取脚纹的ROI区域,最后使用线特征进行识别。识别结果也是令人满意的。更多还原

【Abstract】 In information and network society,there are many occasions in which the personal authentication is required.There is no doubt that biometrics is one of the most important and effective solutions for this task.Generally speaking,biometrics is a field of technology that uses automated methods for identifying or verifying a person based on physiological or behavioral traits such as face,fingerprints,iris and palmprint etc.Due to its importance and promising market prospect,biometrics has been receiving wide attention from researchers.And,the research related to this field is becoming more and more active and hot.Palmprint recognition,developed in recent years,is a new biometrics technology. Compared with fingerprint or iris based personal biometrics system,palmprint based biometrics system has several unique advantages such as stable line features, low-resolution imaging,and easy self positioning etc.More importantly,it can obtain high accurate recognition rate with fast processing speed.Thus,it is very necessary and impending for ones to make a deep study on palmprint recognition.However, palmprint recognition is still staying at the developing stage,and the investigation of its theory and application should be enhanced and improved further.In this thesis, some key techniques of palmprint recognition have been investigated deeply. Particularly,several novel and effective algorithms have been proposed such as recognition methods based on principal lines,orientation code,and appearance etc.The main work in this thesis can be summarized as follows:(1) Line is the basic feature of palmprint.We proposed a novel palmprint verification approach based on principal lines.In feature extraction stage,the modified finite radon transform was proposed,which can extract principal lines effectively and efficiently even in the case that the palmprint images contain many long and strong wrinkles.In matching stage,a novel matching algorithrn was devised to calculate the similarity between principal lines,which has shown good robustness for slight rotations and translations of palmprints.The experimental results for the verification showed that the discriminability of principal lines is also strong.(2) In palmprint recognition field,orientation codes were deemed to be the most promising methods,since the orientation feature contains more discriminative power than other features,and is more robust for the change of illumination.In this thesis, we proposed a novel robust line orientation code for palmprint verification,whose performance is improved by using three strategies.Firstly,the proposed modified finite Radon transform can extract the orientation feature of palmprint more accurately and can solve the problem of sub-sampling better.Secondly,we constructed an enlarged training set to solve the problem of large rotations caused by imperfect preprocessing.Finally,the proposed matching algorithm based on pixel to area comparison had better fault tolerant ability.The experimental results showed that the proposed approach has high recognition rate and fast feature extraction speed.(3) For fast and robust palmprint identification,we developed a new approach, which contains two interesting components.Firstly,the directional representation was proposed for appearance based applications,which is robust to drastic illumination changes and preserves important discriminative information for classification.And then virtual samples were generated to enlarge the training set to compensate matching errors caused by large rotations and translations.Based on these two strategies,the recognition performance of representative appearance based approaches can be improved significantly.Secondly,in order to improve the robustness of palmprint identification,we proposed a fusion method named as Fusion_R combining the proposed appearance based approaches and orientation based approaches,which can obtain very low EER More importantly,we proposed a fast palmprint retrieval scheme named as Fusion_FR,which can obtain very high accuracy recognition rate. Particularly,its matching speed is about 4 times faster than that of Competitive Code, which is one of the approaches with fastest matching speed until to now.(4) A fast palmprint identification approach using a hierarchical retrieval scheme was developed.In the first layer,a fast retrieval method based on the matching of key points of principal lines was proposed for coarse recognition.In this stage,a small database,which contains a lot of training samples with similar structures to test sample,was constructed for subsequent free recognition.In the second layer,Tensor Marginal Fisher Analysis method combining directional representation and enlarged training set was adopted for performing the second retrieval.In the last layer,three approaches i.e.Tensor Marginal Fisher Analysis,Competitive Code and Phase-Only Correlation were fused to form a very robust recognition system.It has been validated that the proposed scheme is effective and efficient by the experiments.(5) An infant biometrics system based on footprint recognition has been developed.Firstly,an infant footprint image acquisition device using digital camera was designed.Secondly,a preprocessing method exploiting the contour of footprint was developed to crop the ROI sub-image.Finally,the footprints can be recognized by means of line feature.The primal experimental results showed that the proposed system is feasible.更多还原