A Novel Image Retrieval Method Using Segmentation and Color Moments

Large image databases are becoming popular due to the ease with which images are beingcreated/digitized and stored. Content Based Image Retrieval (CBIR) has therefore evolved into anecessity. It is a challenging task to design an effective and efficient CBIR system. Current researchworks attempt to obtain the semantics or meaning of the image to perform better retrieval. In this paper,we are going to propose a color image retrieval method based on the primitives of color moments. First,an image is divided into four segments. Then, the color moments of all segments are extracted andclustered into four classes. In this paper mean moments of each class are considered as a primitive of theimage. All primitives are used as features and each class mean combined into single class mean. Thedistance between query image mean with the corresponding database images are calculated by usingSAD method. Experiment results prove that the CBIR using our new measure has better performance thanthe existing methods.