Color Histogram and DBC Co-Occurrence Matrix for Content Based Image Retrieval

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K. Prasanthi Jasmine 1,* P. Rajesh Kumar 1

1. Department of Electronics and Communication Engineering Andhra University, Visakhapatnam Andhra Pradesh, India

* Corresponding author.


Received: 12 Aug. 2014 / Revised: 23 Sep. 2014 / Accepted: 5 Nov. 2014 / Published: 8 Dec. 2014

Index Terms

Color, Directional Binary Code, Texture, Pattern Recognition, Feature Extraction, Local Binary Patterns, Image Retrieval


This paper presents the integration of color histogram and DBC co-occurrence matrix for content based image retrieval. The exit 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. Further, we calculated the co-occurrence matrix to form the feature vector. Finally, the HSV color histogram and the DBC co-occurrence matrix are integrated to form the feature database. The retrieval results of the proposed method have been tested by conducting three experiments on Brodatz, MIT VisTex texture databases and Corel-1000 natural 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.

Cite This Paper

K. Prasanthi Jasmine, P. Rajesh Kumar, "Color Histogram and DBC Co-Occurrence Matrix for Content Based Image Retrieval", International Journal of Information Engineering and Electronic Business(IJIEEB), vol.6, no.6, pp.47-54, 2014. DOI:10.5815/ijieeb.2014.06.06


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