An Efficient Method for Color Images Edge Detection

The purpose of this paper is to show how the edge histogram descriptor for image that can be efficiently utilized for image matching. Since the edge histogram descriptor recommended for the standard represents only local edge distribution in an image, the matching performance for image retrieval may not be satisfactory. In this paper, to increase the matching performance, we propose to use the global and semi-local edge histograms generated directly from the local histogram bins. Then, the global, semi-global, and local histograms of two images are compared to evaluate the similarity measure. Since we exploit the absolute locations of edge in the image as well as its global composition, the proposed matching method is considered to be a more image content-based retrieval. Experimental results support this claim. Experiments on test images for MPEG-7 core experiment show that the proposed method yields better retrieval performance especially for semantic similarity.