CBIR Based on Adaptive Segmentation of HSV Color Space

Abstract

Proposed algorithm is based on color information using HSV color 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 local histogram is used for extracting the maximum color occurrence from each segment. Before extracting the maximum color from each segment the input image is adaptively segmented. Different quantization of hue and saturation are used for partitioning the image into different number of segments. Finally 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.