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구분 SCI
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학술지 Identification of Transformed Image Using the Composition of Features
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양원근, 조아영, 조익환, 오원근, 정동석
멀티미디어학회논문지, v.11 no.6, pp.764-776
08MS3800, Rich UCC 기술 개발(표준화 연계), 오원근
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.
KSP 제안 키워드
Accuracy test, Average intensity, Color characteristics, Data type, Experiment results, Fast matching, Feature Composition, High accuracy, Identification method, Image Identification, Manhattan distance