BCH-LSH: A new scheme of locality-sensitive hashing

Similarity searching of high-dimensional data is fundamental in the multimedia research field. In recent years, the binary code indexing has achieved significant applications in the context of similarity searching. However, most of the existing binary coding methods adopt a random generation method in near neighbour cluster problems, which involve unnecessary computations and degrade similarity in object points. To avoid the uncertainty of random generation codes, in this study, the authors propose a new locality sensitive hashing (LSH) algorithm based on q-ary Bose-Chaudhuri-Hocquenghem (BCH) code. BCH-LSH algorithm utilises the characteristics of the designed distance of BCH codes and uses the BCH codes generator matrix as a transform basis of the hash function to map the source data into the hash space. The experiments show that the BCH-LSH algorithm is superior to the E2LSH algorithm in average precision, average recall ratio and running speed.