• Title/Summary/Keyword: CBIR(Cotent based image retreival)

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Improved Bag of Visual Words Image Classification Using the Process of Feature, Color and Texture Information (특징, 색상 및 텍스처 정보의 가공을 이용한 Bag of Visual Words 이미지 자동 분류)

  • Park, Chan-hyeok;Kwon, Hyuk-shin;Kang, Seok-hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.79-82
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    • 2015
  • Bag of visual words(BoVW) is one of the image classification and retrieval methods, using feature point that automatical sorting and searching system by image feature vector of data base. The existing method using feature point shall search or classify the image that user unwanted. To solve this weakness, when comprise the words, include not only feature point but color information that express overall mood of image or texture information that express repeated pattern. It makes various searching possible. At the test, you could see the result compared between classified image using the words that have only feature point and another image that added color and texture information. New method leads to accuracy of 80~90%.

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