Histogram-Based Color Image Retrieval

In this project, six histogram-based search methods are investigated in two different color spaces, RGB and HSV. Histogram search characterizes an image by its color distribution, or histogram but the drawback of a global histogram representation is that information about object location, shape, and texture is discarded. Thus this project showed that images retrieved by using the global color histogram may not be semantically related even though they share similar color distribution in some results. An image retrieval demo system was built to make it easy to test the retrieval performance and to expedite further algorithm investigation. And six histogram-based image retrieval methods in two color spaces were exhaustively compared by providing precision vs. recall graphs for each image class and for all test images. In general, histogram-based retrievals in HSV color space showed better performance than in RGB color space. The hitogram Intersection-based image retrieval in HSV color space was found to be most desirable among six retrieval methods. Table of