Application of Local Color Features in Content-based Image Retrieval
Ming Zhang · Jisuanji gongcheng · 2004
Global Color histogram is often used in content based image retrieval. But this method cant contain the spatial features. So different images may have the same color histogram. The local histogram partitioning an image into regions takes the spatial features into account, but fails to find rotated or translated images that are similar to query images. In this paper, a new method for image retrial using color moments of partitions and minimum cost perfect matching for a weighted bipartite graph based on image segmentation is proposed. This method of similarity measurement takes into account both the spatial features and the invariance of rotation and translation. Finally experiments show that the improvement of similarity measurement based on local color features is very effective.