DBC Co-occurrence Matrix for Texture Image Indexing and Retrieval

  • K. Prasanthi Jasmine
  • P. Rajesh Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)


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.


Directional binary code Texture Pattern recognition Feature extraction Local binary patterns Image retrieval 


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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringAndhra UniversityVisakhapatnamIndia

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