HSV Color Histogram and Directional Binary Wavelet Patterns for Content Based Image Retrieval

This paper presents a new image indexing and retrieval algorithm by integrating color (HSV color histogram) and texture (directional binary wavelet patterns (DBWP)) features. For color feature, first the RGB image is converted to HSV image, and then histograms are constructed from HSV spaces. For texture feature, an 8-bit grayscale image is divided into eight binary bit-planes, and then binary wavelet transform (BWT) on each bitplane to extract the multi-resolution binary images. The local binary pattern (LBP) features are extracted from the resultant BWT sub-bands. Two experiments have been carried out for proving the worth of our algorithm. It is further mentioned that the database considered for experiments are Corel 1000 database (DB1), and MIT VisTex database (DB2). The results after being investigated show a significant improvement in terms of their evaluation measures as compared to HSV histogram and DBWP. KeywordsDirectional Binary Wavelet Patterns (DBWP); Local Binary Patterns (LBP); Feature Extraction; HSV histogram; Image Retrieval.