3D Palmprint Identification Using Block-Wise Features and Collaborative Representation
3D Palmprint Identification Using Block-Wise Features and Collaborative Representation
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DOI：
10.1109/tpami.2014.2372764
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发表时间：
2015-08
影响因子：
23.6
通讯作者：
Lin Zhang;Ying Shen;Hongyu Li;Jianwei Lu
中科院分区：
文献类型：
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作者：
Lin Zhang;Ying Shen;Hongyu Li;Jianwei Lu
近年来，开发3D掌纹识别系统开始受到研究人员的关注。与2D掌纹相比，3D掌纹有几个独特的优点。然而，现有的3D掌纹匹配方法大多是针对一对一的验证而设计的，对于一对多的识别情况效率不高。在本文中，我们提出了一个基于协作表示（CR）的框架，该框架具有11范数或12范数正则化，用于3D掌纹识别，填补了这一空白。实验中对不同正则化项的效果进行了评价。为了使用基于cr的分类框架，一个关键问题是如何提取特征向量。为此，我们提出了一种基于分块统计的特征提取方案。我们将三维掌纹ROI划分为均匀块，并从每个块中提取表面类型的直方图；然后将所有块的直方图连接起来形成特征向量。这种特征向量具有高度的判别性，并且对仅仅的不对齐具有鲁棒性。实验表明，该框架具有12范数正则化项，识别精度明显高于其他方法。更重要的是，它的计算复杂度极低，非常适合大规模的识别应用。源代码可从http://sse.tongji.edu.cn/linzhang/cr3dpalm/cr3dpalm.htm获得。
Developing 3D palmprint recognition systems has recently begun to draw attention of researchers. Compared with its 2D counterpart, 3D palmprint has several unique merits. However, most of the existing 3D palmprint matching methods are designed for one-to-one verification and they are not efficient to cope with the one-to-many identification case. In this paper, we fill this gap by proposing a collaborative representation (CR) based framework with l1-norm or l2-norm regularizations for 3D palmprint identification. The effects of different regularization terms have been evaluated in experiments. To use the CR-based classification framework, one key issue is how to extract feature vectors. To this end, we propose a block-wise statistics based feature extraction scheme. We divide a 3D palmprint ROI into uniform blocks and extract a histogram of surface types from each block; histograms from all blocks are then concatenated to form a feature vector. Such feature vectors are highly discriminative and are robust to mere misalignment. Experiments demonstrate that the proposed CR-based framework with an l2-norm regularization term can achieve much better recognition accuracy than the other methods. More importantly, its computational complexity is extremely low, making it quite suitable for the large-scale identification application. Source codes are available at http://sse.tongji.edu.cn/linzhang/cr3dpalm/cr3dpalm.htm.