中文摘要：

目的将韦伯局部描述子WLD（Weber local descriptor）应用于掌纹识别，并针对掌纹具有丰富线特征的特点，在WLD基础上改进获得线特征韦伯局部描述子LWLD（1ine feature weber local descriptor），以提高掌纹识别的效率。方法首先采用MFRAT或Gabor滤波器对掌纹图像进行线性滤波，生成方向图和能量图；然后对能量进行韦伯差分激励滤波生成差分激励图；最后，基于方向图和差分激励图构造线韦伯特征直方图，并基于线韦伯特征直方图进行掌纹特征识别。结果基于Poly Ⅱ和Cross—Sensor掌纹库进行对比实验，采用曼哈顿距离和卡方距离进行匹配，其中在PolyaⅡ库上的识别率最高均达到100％，在识别率和容错性方面均优于其他主要基于局部描述子的识别方法。结论首次将韦伯局部描述子引入掌纹识别领域，发展了一种新的基于局部描述子的掌纹识别方法。和其他基于局部描述子的掌纹识别算法相比，本文方法具有更高识别率和稳定性。

英文摘要：

Objective Given the advantages of low computation cost and absence of a training requirement, local descriptor- based palmprint recognition methods are eliciting an increasing amount of attention. The Weber local descriptor （WLD） is a newly presented local descriptor inspired by Weber＇ s law in psychology. This study applies WLD to palmprint recogni- tion. To improve palmprint recognition performance, a line feature WLD is presented by considering the sufficient line fea- tures of a palmprint. Method First, modified finite random transform or the Gabor filter is applied to a palmprint image to generate directional image q~ and energy image E. Second, energy image E is convoluted by the Weber operator to generate differential excitation image. Finally, based on directional image and differential excitation image , the histogram of the line Weber local feature can be constructed for use in palmprint recognition. Result The Polytechnic University Palmprint Database Ⅱ and the Cross-Sensor Palmprint Database are utilized in an experiment on Polyu Ⅱ database. The proposed method can achieve 100% identification rate with both Manhattan and chi-square distance. Results demonstrate that the presented method has a high identification rate and is robust. Conclusion This study introduces WLD into palmprint recog- nition to develop a new palmprint recognition method based on a local descriptor. Compared with other palmprint recognition methods based on a local descriptor, the presented method has a higher identification rate and is more robust.