An Image Removal Using Local TetraPatterns for Content Based Image Retrieval

Abstract

Content-based image retrieval is a technique of automatic retrieval of images from large database that perfectly matches the query image. For the large database, many of the research works had been undertaken in the past decade to design efficient image retrieval system. On many fields such as industry, education, biomedical and research the amount of image data that has to be stored, managed, searched and retrieved grows continuously. In this paper, we propose a new image retrieval technique for Content-based image retrieval (CBIR) using local tetra pattern (LTP). The local tetra pattern (LTP) and local binary pattern (LBP) determines the correlation on grey level difference between referenced pixel and its surrounding neighbours. The proposed technique encodes the relationship between the referenced pixel and its neighbours and by via first-order derivatives in vertical and horizontal directions. The proposed algorithm has been experienced on different real images and its performance is found to be somewhat acceptable when compared with performance of conventional technique of content based image retrieval. In terms of average precision and average recall we calculated the performance of proposed method.