Research on image retrieval algorithm based on LBP and LSH

Abstract

Using LBP (local binary pattern) to extract texture feature in the area of image recognition and retrieval has achieved good results. LSH (locality sensitive hashing) in the information retrieval, especially to solve the ANN (approximate nearest neighbor) problem has a more important Status. LSH has a solid theoretical basis and excellent performance in high-dimensional data space. Under the trend of cloud computing and Big Data, this paper proposes an image retrieval algorithm based on LBP and LSH. Firstly, LBP is used to extract the texture feature vector of the image. Then, the LBP texture feature is reduced dimensionally and indexed into different buckets using LSH. Finally, the image corresponding to the index value in the bucket is extracted for second retrieval by using LBP. This algorithm can adapt to the massive image retrieval and ensures the high accuracy of the image retrieval and reduces the time complexity. This algorithm is of great significance.