Abstract
One of the most significant current discussions in image processing is a document analysis. Now, many types of document database were established in order to address the issue of binarization effectiveness. In this paper, a comprehensive review of the document database was presented. Review based on an image from Document Image Binarization Contest (DIBCO) from 2013 to 2017 which consists of handwritten and printed image. The best algorithm for each year is discussed and analyzed. Based on the results, the technique using background estimation and stroke edges is better performance for the overall database. Besides, the method using the combination of Laplacian operator and canny edge detection also shows the successful result, especially in the printed image. Implications of the review give the direction for future binarization approach developments.
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