<![CDATA[Image retrieval system is a method used to extract image features and provides rules for comparing two images based on these characteristics. Several methods that can be used are Image Meta Search and Content-Based Image Retrieval (CBIR) methods. CBIR is an image search based on information contained in the image, for example searching for duck images, then entering the characteristics of the duck image and then based on these characteristics look for another image with similar features. Characteristics commonly used to help search for images include color, shape and texture features. In the design of this image retrieval application program, the characteristic used is the color feature. One method that can be used to calculate image characteristics is the Color Histogram Peaks Indexing. This method will compare the image to be searched (query image) with the database image (image stored in the database) to produce color features that will be used as feature vectors for query images and database images. The Color Histogram Peaks Indexing method is a new method designed to overcome the problem of scaling changes in image search. Based on the test results, it is known that the conversion process from HSV image to RGB image requires a long calculation process because it has to do repetition for each pixel, the scale difference of an image will not greatly affect the location of the peak on the HSV Histogram image and image retrieval algorithm can be used to perform Image search process based on the color characteristics of the image.]]>
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