Extracting Color Using Adaptive Segmentation for Image Retrieval

In this paper we address the issue of image database retrieval based on color using HSV information space. 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 we used local histogram to extract the maximum color occurrence from each segment. Before extracting the maximum color from each segment the input image is converted to HSV and adaptive segmentation is applied on the HSV color space. This will compute the feature vector. Different quantization of hue, saturation and value are used. Minkowski metric is used for feature vector comparison. Web based image retrieval demo system is built to make it easy to test the retrieval performance and to expedite further algorithm investigation.