Color-based clustering for text detection and extraction in image

  • Authors:

  • Jian Yi;Yuxin Peng;Jianguo Xiao

  • Affiliations:

  • Peking University, Beijing, China;Peking University, Beijing, China;Peking University, Beijing, China

  • Venue:
  • Proceedings of the 15th international conference on Multimedia
  • Year:
  • 2007

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Abstract

This paper proposes a new approach for the text detection and extraction in image. The novelty of our approach mainly lies in the color-based clustering into two phases: In text detection phase, we consider jointly the two significant features of text regions in image: homogeneous color and sharp edges, and color-based clustering is employed to decompose the color edge map of image into several edge maps, which makes the text detection of image more accurate. In text extraction phase, on one hand, for effective text recognition, we consider the color difference between the text and background in image, and color-based clustering is utilized to remove image noise. Another hand, for effective binarization of text region, instead of performing binarization in a constant color plane as in the existing methods, our approach can adaptively select the best color plane according to the text contrast difference among color planes for binarization. Experimental results show our approach is better than the existing methods.