Robust image retrieval approach based on clustering analysis of re-quantized color image
In this paper, we propose a robust approach about color image retrieval. It can realize fast matching in CBIR (Content-Based Image Retrieval) when we search in large image databases. Indexes root in object features of Z image which is the result of re-quantization in HSV color space, matching with a non-geometrical distance is based on objects, so time consumption pixel by pixel can be avoided. Because Z image is made up of many color clustering regions and invariant moments are used for feature representation, our approach is robust to translation, scale and rotation.
robustness clustering cbir non-geometrical distance quantization