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DOI: 10.14569/IJACSA.2017.080938
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Colored Image Retrieval based on Most used Colors

Author 1: Sarmad O. Abter
Author 2: Dr. Nada A.Z Abdullah

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 9, 2017.

  • Abstract and Keywords
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Abstract: The Fast Development of the image capturing in digital form leads to the availability of large databases of images. The manipulation and management of images within these databases depend mainly on the user interface and the search algorithm used to search these huge databases for images, there are two search methods for searching within image databases: Text-Based and Content-Based. In this paper, we present a method for content-based image retrieval based on most used colors to extract image features. A preprocessing is applied to enhance the extracted features, which are smoothing, quantization and edge detection. Color quantization is applied using RGB (Red, Green, and Blue) Color Space to reduce the range of colors in the image and then extract the most used color from the image. In this approach, Color distance is applied using HSV (Hue, Saturation, Value) color space for comparing a query image with database images because it is the closest color space to the human perspective of colors. This approach provides accurate, efficient, less complex retrieval system.

Keywords: Most used colors feature; color histogram; content-based image retrieval (CBIR); contour analysis; HSV color space

Sarmad O. Abter and Dr. Nada A.Z Abdullah, “Colored Image Retrieval based on Most used Colors” International Journal of Advanced Computer Science and Applications(IJACSA), 8(9), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080938

@article{Abter2017,
title = {Colored Image Retrieval based on Most used Colors},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080938},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080938},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {9},
author = {Sarmad O. Abter and Dr. Nada A.Z Abdullah}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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