Abstract— This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.
Index Terms— Content based image retrieval (CBIR); HSV color space; Regions of Interest; Colour histogram; Euclidean distance; GLCM.
Cite: E R Vimina and K Poulose Jacob, "Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest," Journal of Image and Graphics, Vol. 1, No. 1, pp. 7-11, March 2013. doi: 10.12720/joig.1.1.7-11
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