Browse > Article

Analysis of Image Identifier Generation Methods for Various Size Patterns  

Park, Je-Ho (Dankook University, Computer Science)
Publication Information
Journal of the Semiconductor & Display Technology / v.9, no.4, 2010 , pp. 51-56 More about this Journal
Abstract
As the price of image acquisition component becomes low enough, the compact and easily accessible handheld devices are generally equipped with image acquisition functionality. This trend speeds up various applications in diverse areas such as image related services and software. Therefore users strongly need to identify their images effectively and efficiently so that the duplicated images are perceived as one physical entity. In order to handle this environment, we propose a number of methods that generate image identifiers utilizing fundamental image features. In this paper, we analyze the identifier generation methods in terms of various size patterns, especially for tiny size cases, since the small images does not contain abundant pixels for feature extraction. In this paper, experimental evaluation over identifier generation methods' behavior according to different sizes is demonstrated.
Keywords
Image; Identifier; Linear; Database; Resolution; Size;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 M.G. Bantum, US Patent 5,887,081, 1999.
2 S. Pabboju and A. Reddy, "A novel approach for content-based image indexing and retrieval system using global and region features", IJCSNS, Vol. 9, No. 2, 2009.
3 J. Berens, G.D. Finlayson and G. Qiu, "Image indexing using compressed color histograms", IEE Proc. of Vision, Image and Signal Processing, Vol. 147, No. 4, pp.349-355, 2000.
4 Y. Gong, C.H. Chuan and G. Xiaoyi, "Image indexing and retrieval based on color histograms", Multimedia Tools and Applications, Vol. 2, No. 2, pp.133-156, 1996.
5 송치일, 낭종호, "MPEG-7 시각 정보 기술자의 인덱싱 및 결합 알고리즘", 정보과학회논문지: 소프트웨어 및 응용, 제 34권, 제1호, 1-10쪽, 2007.   과학기술학회마을
6 M. Haseyama and I. Kondo, "2-D functional AR model for image identification", Proceedings of the 2003 International Conference on Multimedia and Expo, pp.377-380, 2003.
7 R.C. Gonzalez, "Digital Image Processing (3rd Ed.)", Prentice Hall, 2007.
8 J. Illingworth and J. Kittler, "A survey of efficient hough transform methods", Computer Vision, Graphics, and Image Processing, Vol. 44, No. 1, pp.87-116, 1988.   DOI   ScienceOn
9 S.K. Naik and C.A. Murthy, "Hough transform for region extraction in color images", Proc. of the Fourth Indian Conference on Computer Vision, Graphics and Image Processing, pp.252-257, Kolkata, India, 2004.
10 http://www.netgraphics.sk
11 G. Bradski and A. Kaehler, "Learning OpenCV", O'Reily Media, 2008.