Meaningful regions-based algorithm for color image retrieval
基于有意义区域的颜色检索算法

An meaningful regions-based algorithm was provided: the color cluster parameters of images were calculated first.Those images with high value were split into sub-regions by image segmentation,and others were just split into sub-blocks.Each block was regarded as a region,and was given a dynamic weight.The total similarity between two images was computed according to those regions' color histograms.The experiments show that this approach can achieve increased power of discrimination than the classical color histogram method.