Features Defined by Median Filtering on RGB Segments for Image Retrieval

The performance of image retrieval using median filtering on RGB color information was analyzed in this paper in order to design a more effective algorithm for extracting features from color images for image retrieval. We propose an image retrieval technique, which uses features obtained by indexing color information. The method uses size order and quantization after intermediate values are extracted for each RGB image and partitioned into regular sized blocks. Small feature table based on color image features are proposed in this paper, because even an effective feature extraction algorithm requires a large amount of storage space and calculation. Matches were obtained by comparing normalized values of features that were organized into a table using the proposed algorithm, for the input image and existing images and reorganizing into a table that can use correlogram.