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首页> 外文会议>2016 International Conference on Biometrics >Binary search path of vocabulary tree based finger vein image retrieval
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Binary search path of vocabulary tree based finger vein image retrieval

机译：基于词汇树的手指静脉图像检索的二元搜索路径

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摘要

Many related studies have reported promising results in finger vein recognition, but it is still challenging to perform robust image retrieval, especially in the application scenarios with large scale populations. With the purpose in consideration, this paper presents a binary search path of hierarchical vocabulary tree based finger vein image retrieval method. In detail, a vocabulary tree is built based on the local finger vein textons by the hierarchical k-means method. Each image patch is represented by the binary path in the search of its most similar leaf node, and the value of each bit in the path is labeled as 1 or 0 according to whether the corresponding node is passed or skipped in search. The similarity of two images is defined as the number of overlapped bits in all involved path pairs. And, the enrolled images with top t scores in the sorted score vector will be selected as candidates to narrow the search space. Experimental results on five finger vein databases confirm that the proposed method can improve the retrieval performance on both accuracy and efficiency.
机译：许多相关研究已经报道了在指静脉识别方面的有希望的结果，但是执行鲁棒的图像检索仍然具有挑战性，尤其是在人口众多的应用场景中。考虑到此目的，本文提出了一种基于分层词汇树的手指静脉图像检索方法的二进制搜索路径。详细地，通过分层的k-means方法，基于局部手指静脉纹理建立词汇树。每个图像块在其最相似的叶节点的搜索中由二进制路径表示，并且路径中每个位的值根据在搜索中是通过还是跳过了相应的节点而标记为1或0。将两个图像的相似性定义为所有涉及的路径对中重叠比特的数量。并且，在排序的分数向量中具有最高t分数的已注册图像将被选择为候选者，以缩小搜索空间。在五个手指静脉数据库上的实验结果证实，该方法可以提高检索准确性和效率。

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