Paper Title
Content Based Image Retrieval Algorithm Using Local Tetra Texture Features

Abstract - In this paper, Content Based Image Retrieval gives the path to retrieve the needed information based on the image content. The earlier version of CBIR was based on Local Binary Pattern, Local Derivative Pattern and Local Ternary Pattern. These methods extort information based on the distribution of edges, which are coded using only two directions. The performances of these methods are tiny less and thus it can be improved by differentiating the edges in more than two directions. The performance is improved by four direction code, so called local tetra pattern (LTrPs) for CBIR. This method encodes the connection between the referenced pixel and its neighbors based on the directions that are calculated using the first-order derivatives in vertical and horizontal directions. This project proposes generic strategy to compute LTrP during horizontal, vertical and diagonal derivatives.