Image Retrieval Algorithm Based on Minimal Loss Hashing

Abstract

In order to solve the inefficiency and time-consuming of traditional image retrieval algorithms, an image retrieval algorithm based on minimal loss hashing is proposed. Firstly, the original high dimensional data is reduced by principal component analysis and Laplacian Eigenmaps. Secondly, minimize dimensionality reduction and quantization coding loss function, then we could obtain the hash function by iterative optimization parameters. Finally, the original data matrix is converted into a hash coding matrix, and the sample similarity is obtained by calculating the Hamming distance between samples. The experimental results on four public datasets show that the proposed method improves the retrieval performance.