Content Based Image Retrieval by Combining Median Filtering, BEMD and Color Technique
A Content Based Image Retrieval (CBIR) system provides an efficient way of retrieving most similar images from image collections. In this paper we present a novel approach which combines color and edge features to extract similar images. We apply median filtering technique to original image to get the smoothed image. The Bi-directional Empirical Mode Decomposition (BEMD) technique is applied to extract edge information from the image. Then we replace only the values of edge position of smoothed image with the detected edge image values by BEMD and extracted 64 bins gray features. Later we apply one dimensional color histogram technique to obtain histogram vector by using RGB color space and is converted into 32 bins color features. Finally, we combine both the features to extract the most similar images from the database. The experiment is conducted on 1000 images of different categories stored in groundtruth database and the effectiveness of this technique is demonstrated. The results have been tabulated and compared with the conventional median and edge technique. We can observe that performance our proposed method is good.
KeywordsCBIR BEMD Indexing Image database Histogram Color
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