DBC Co-occurrence Matrix for Texture Image Indexing and Retrieval

Abstract

In this paper, a new image indexing and retrieval algorithm using directional binary code (DBC) co-occurrence matrix is proposed. The exits DBC collect the directional edges, which are calculated by applying the first-order derivatives in 0o, 45o, 90o, and 135o directions. The feature vector length of DBC for a particular direction is 512, which are more for image retrieval. To avoid this problem, we collect the directional edges by excluding the center pixel and further applied the rotation invariant property. Finally, we calculated the co-occurrence matrix to form the feature vector. The retrieval results of the proposed method have been tested by conducting the experiment on Brodatz texture database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP, DBC, and other transform domain features.