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GLOBAL MEASURE ON IMAGE CONTENT

GLOBAL MEASURE ON IMAGE CONTENT
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摘要 This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms were used to extract texture feature of the image and the average color was used to extract the color features. The principle component of the feature vector of image can be constructed. Content based image retrieval was performed by comparing the feature vector of the query image with the projection feature vector of the image database on the principle component space of the query image. By this technique, it can reduce the dimensionality of feature vector, which in turn reduce the searching time. This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms were used to extract texture feature of the image and the average color was used to extract the color features. The principle component of the feature vector of image can be constructed. Content based image retrieval was performed by comparing the feature vector of the query image with the projection feature vector of the image database on the principle component space of the query image. By this technique, it can reduce the dimensionality of feature vector, which in turn reduce the searching time.
作者 李介谷
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2000年第2期108-111,共4页 上海交通大学学报(英文版)
关键词 content based image RETRIEVAL PRINCIPLE component analysis AVERAGE color texture GABOR WAVELET TRANSFORM Document code:A content based image retrieval principle component analysis average color texture Gabor wavelet transform Document code:A
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参考文献7

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