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An image retrieval system based on the feature of color differences among the edges of objects
Keywords:
image retrieval, color-based image retrieval, color attribute, color histogramAbstract
This paper focuses on color differences among the edges of objects in an image. The variations of colors among the objects in the image can depict the directions and simple geometric shapes of most objects in the image regardless of the influence from the shift variant of objects and scale variant in the image. Based on the feature of color differences among the edges of objects, this paper constructs an image retrieval system. Experimental results show that this system can effectively and quickly deliver the desired database images to the users
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References
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[12] M. Stricker, and M. Swan, “The Capacity of Color Histogram Indexing,” Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Seattle, Washington,
[2] S. Bandyopadhyay, and U. Maulik, “An Evolutionary Technique Based on K-Means Algorithm for Optimal Clustering in RN,” Information Sciences, Vol. 146, Issue: 1-4, October 2002, pp. 221-237.
[3] R. Brunelli, and O. Mich, “Histograms Analysis for Image Retrieval,” Pattern Recognition, Vol. 34, 2001, pp. 1625-1637.
[4] Y. K. Chan, and C. C. Chang, “A Color Image Retrieval System Based on the Run-Length Representation,” Pattern Recognition Letter, Vol. 22, 2001, pp. 447-455.
[5] C. C. Chang, and Y. K. Chang, “A Fast Filter for Image Retrieval Based on Color-Spatial Features,” SEMA2000, Baden-Baden, German, July 2000, pp. 47-51.
[6] T. Chan, and L. H. Chen, “Fast Mapping Algorithm for Histogram to Binary Set Conversion,” Pattern Recognition Letter, Vol. 21, 2000, pp.899-906.
[7] K. Eukunaga, Introduction to Statistical Pattern Recognition, San Diego, CA., Academic Press, 1990.
[8] W. J. Kuo, “Study on Image Retrieval and Ultrasonic Diagnosis of Breast Tumors,” Dissertation, Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan, R.O.C, January 2001.
[9] M. Sánchez, and J. Francisco, “Automatic Recognition of Biological Shapes with and without Representations of Shape,” Artificial Intelligence in Medicine, Vol. 18, Issue: 2, February 2000, pp. 173 – 186.
[10] H. S. Sawhney, and J. L. Hafner, “Efficient Color Histogram Indexing,” Proceedings of IEEE International Conference on Image Processing, Vol. 2, Austin, Texas, November 1994, pp. 66-77.
[11] K. Shearer, S. Venkatesh, and D. Kieronska, “Spatial Indexing for Video Databases,” Journal of Visual Communication and Image Representation, Vol. 7, No. 4, 1996, pp. 325-335.
[12] M. Stricker, and M. Swan, “The Capacity of Color Histogram Indexing,” Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Seattle, Washington,
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Published
2005-04-01
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[1]
“An image retrieval system based on the feature of color differences among the edges of objects”, JCS&T, vol. 5, no. 01, pp. p. 25–29, Apr. 2005, Accessed: Mar. 12, 2026. [Online]. Available: https://journal.info.unlp.edu.ar/JCST/article/view/884
