Binary search path of vocabulary tree based finger vein image retrieval

Abstract

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.