Image Semantic Classification by Using SVM
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    Abstract:

    There exists an enormous gap between low-level visual feature and high-level semantic information, and the accuracy of content-based image classification and retrieval depends greatly on the description of low-level visual features. Taking this into consideration, a novel texture and edge descriptor is proposed in this paper, which can be represented with a histogram. Furthermore, with the incorporation of the color, texture and edge histograms seamlessly, the images are grouped into semantic classes using a support vector machine (SVM). Experiment results show that the combination descriptor is more discriminative than other feature descriptors such as Gabor texture.

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万华林,Morshed U. Chowdhury.基于支持向量机的图像语义分类.软件学报,2003,14(11):1891-1899

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History
  • Received:September 28,2002
  • Revised:December 04,2002
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