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Authors
Affiliations
1 Department of ECE, Malla Reddy College of Engineering & Technology, Hyderabad, Telangana, IN
Source
International Journal of Research in Signal Processing, Computing & Communication System Design, Vol 3, No 2 (2017), Pagination: 22-25
Abstract
It has very important practical significance to analyze and research minority costume from the perspective of computer vision for minority culture protection and inheritance. As first exploration in minority costume image retrieval, this Project proposed a novel image feature representation method to describe the rich information of minority costume image. Firstly, the color histogram and edge orientation histogram are calculated for divided sub-blocks of minority costume image. Then, the final feature vector for minority costume image is formed by effective fusion of color histogram and edge orientation histogram. Finally, the improved Canberra distance is introduced to measure the similarity between query image and retrieval image. We have evaluated the performances of the proposed algorithm on self-build minority costume image dataset, and the experimental results show that our method can effectively express the integrated feature of minority costume images, including color, texture, shape and spatial information. Compared with some conventional methods, our method has higher and stable retrieval accuracy.
Keywords
Color Histogram, Edge Orientation, Histogram of Oriented Gradients (HOG), Local Directional Patterns (LDP).
References
- M. J. Swain, and D. H. Ballard, “Color indexing,” International Journal of Computer Vision, vol. 7, no. 1, pp. 11-32, 1991.
- M. Stricker, and M. Orengo, “Similarity of color images,” In SPIE Conference on Storage and Retrieval for Image and Video Databases, San Jose, USA, vol. 2420, pp. 381-392, 1995.
- G. Pass, R. Zabin, and J. Miller, “Comparing images using color coherence vectors,” In ACM International Conference on Multimedia, Boston, MA, pp. 65-73, 1996.
