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서지반출
Identification of Transformed Image Using the Composition of Features
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취소
  • Identification of Transformed Image Using the Composition of Features
  • Identification of Transformed Image Using the Composition of Features
저자명
Yang. Won-Keun,Cho. A-Young,Cho. Ik-Hwan,Oh. Weon-Geun,Jeong. Dong-Seok
간행물명
멀티미디어학회논문지
권/호정보
2008년|11권 6호|pp.764-776 (13 pages)
발행정보
한국멀티미디어학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Image identification is the process of checking whether the query image is the transformed version of the specific original image or not. In this paper, image identification method based on feature composition is proposed. Used features include color distance, texture information and average pixel intensity. We extract color characteristics using color distance and texture information by Modified Generalized Symmetry Transform as well as average intensity of each pixel as features. Individual feature is quantized adaptively to be used as bins of histogram. The histogram is normalized according to data type and it is used as the signature in comparing the query image with database images. In matching part, Manhattan distance is used for measuring distance between two signatures. To evaluate the performance of the proposed method, independent test and accuracy test are achieved. In independent test, 60,433 images are used to evaluate the ability of discrimination between different images. And 4,002 original images and its 29 transformed versions are used in accuracy test, which evaluate the ability that the proposed algorithm can find the original image correctly when some transforms was applied in original image. Experiment results show that the proposed identification method has good performance in accuracy test. And the proposed method is very useful in real environment because of its high accuracy and fast matching capacity.