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This paper proposes COCOCLUST, a contour-based color clustering method which robustly segments and binarizes colored text from complex images. Rather than operating on the entire image, a ‘small’ representative set of color pixels is first identified using the contour information. The method involves the following steps: (i) Identification of prototype colors (ii) A one-pass algorithm to identify color clusters that serve as seeds for the refining step using kmeans clustering (iii) Assignment of pixels in the original image to the nearest color cluster (iv) Identification of potential candidate text regions in individual color layer and (v) Adaptive binarization. We propose a robust binarization technique to threshold the identified text regions, taking into account the presence of inverse texts, such that the output image always has black text on a white background. Experiments on several complex images having large variations
in font, size, color, orientation and script illustrate the robustness of the method

Added on August 20, 2014

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  • Product Type : Research Paper
  • License Type : Freeware
  • System Requirement : Not Applicable
  • Author : T Kasar, A G Ramakrishnan
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