Non-negative locality-constrained vocabulary tree for finger vein image retrieval

Non-negative locality-constrained vocabulary tree

for finger vein image retrieval

Kun SU;Gongping YANG;Lu YANG;Peng SU;Yilong YIN

【期刊名称】《中国高等学校学术文摘·计算机科学》 【年(卷),期】2019(013)002

【摘要】Finger vein image retrieval is a biometric identification technology that has recently attracted a lot of attention.It has the potential to reduce the search space and has attracted a considerable amount of research effort recently.It is a challenging problem owing to the large number of images in biometric databases and the lack of efficient retrieval schemes.We apply a hierarchical vocabulary tree modelbased image retrieval approach because of its good scalability and high efficiency.However,there is a large accumulative quantization error in the vocabulary tree (VT) model that may degrade the retrieval precision.To solve this problem,we improve the vector quantization coding in the VT model by introducing a non-negative locality-constrained constraint:the non-negative locality-constrained vocabulary tree-based image retrieval model.The proposed method can effectively improve coding performance and the discriminative power of local features.Extensive experiments on a large fused finger vein database demonstrate the superiority of our encoding method.Experimental results also show that our retrieval strategy achieves better performance