A novel approach for document image binarization

Extraction of text from badly degraded image document is a very challenging task due to the variation between the foreground and background text of various document images. The proposed system tackle this problem by the combination of several state of-the-art binarization methodologies as well as on the efficient incorporation of the edge information of the gray scale source image. Given a degraded document image an adaptive contrast map is first constructed. The contrast map is then binarized and combined with Canny´s edge map to identify the text stroke edge pixels. The document text is further extracted using globally matched wavelet filters. Finally fisher classifier is used for improving the result of image segmentation. The approach is simple, robust and applicable to images of typewritten text as well as hand written text or a mixture of both. Experimental results shows that the proposed method gives superior performance compared with other techniques.