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• W1170417004 abstract "Image retrieval based on the color histogram is one of the technologies based on the content. The processing time of the method is shorter and easy to implement, but its precision need to be improved. In this paper, the algorithm is improved. The same image library is retrieved by the image retrieval method based on cumulative histogram and the normalized cumulative histogram. The recall and precision are obviously improved. The results show that the improved image retrieval algorithm based on the color histogram is more effective. Introduction In recent years the information technology is developed rapidly. How to get the useful information from the vast image library is the focus of research in recent years. The color, texture and shape of the image characteristics are more intuitive and more important. The color histogram meaning the pixel distribution is extracted simply and be not sensitive to rotation. So the image retrieval based on the content is used widely. Color is the most significant underlying characteristic of image. The histogram based on global color is the most classic image retrieval. The method is quick and easy, but it can’t reflect the color spatial information. Later, many improved histograms based on histogram are proposed. The algorithm based on space model is adopted by literature 3. The changing information of image edge is described, but the color information of the edge is not considered.The image retrieval algorithm based on image edge is adopted by literature 4. The color, direction and the space of image is not considered. The improved algorithm based on color component quantization image retrieval is put forward in the paper above analysis. Feature Extraction and Quantitative In the common color space model, the RGB color space model is difference from the human eye perception largely. The shade, brightness and saturation of the HSV color space model are more compared with human visual perception. So the RGB model is converted to the HSV model in order to represent the image features effectively. In HSV space, in order to reduce dimension and calculation, the H channel, S and V channel converted need to be quantified. Assuming that quantitative values are 8,3and 3 respectively, the 72-dimensional color histogram can be obtained finally. If the position any pixel in image is set to ( , ) x y , the corresponding value of each pixel is { } ( , ) , 1, 2, ,72 HSV x y n n = ∈  . First, the histogram of H component, S component and V component is got by calculating. The formula corrected by gamma is as follows:" @default.
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• W1170417004 date "2015-01-01" @default.
• W1170417004 modified "2023-09-23" @default.
• W1170417004 title "An Improved Image Retrieval Based on Color Histogram" @default.
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• W1170417004 doi "https://doi.org/10.2991/isrme-15.2015.183" @default.
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