Deep Supervised Binary Hash Codes for Footprint Image Retrieval

Abstract

Footprints can provide strong evidence for the detection of criminal cases, and the similarity retrieval of footprint images is generally carried out using hand-extracted image features, which have problems such as low retrieval matching accuracy and slow retrieval speed. In order to solve the above problems, a footprint image retrieval method based on deep supervised binary hash(DSBH) is proposed, and the feature extraction of footprint image is carried out by using the convolutional neural network, which can be combined with the deep hash algorithm to solve the retrieval problem of footprint image. The experimental results can reach 0.980, which proves the effectiveness of this method.