抽象的な

Texture Extraction for Image Retrieval Using Local Tetra Pattern

Nitin Narayankar, Sanjay Dhaygude

Content Based Image Retrieval(CBIR) is one of the prominent area to retrieve images from a large collection of database. There is wide range of texture analysis techniques used for feature extraction of an image. In this paper, we have proposed image indexing and retrieval algorithm for texture extraction using Local tetra pattern (LTrP). The local binary pattern (LBP) and local ternary pattern (LTP) encode the texture features of an image depending on the grey level difference between reference pixel and its neighbors. The LTrP encodes the relationship between the reference pixel and its neighbors by using the first-order derivatives in vertical and horizontal directions. Local tetra pattern (LTrP) extracts information based on the distribution of edges which are coded using four directions. To get the retrieval result we used Corel 1000 database. The performance of the proposed method is measured in terms of average precision and average recall. The performance analysis shows that the proposed method improves the retrieval result as compared with standard LBP.