Comparative study of different binarization methods through their effects in characters localization in scene images

In this paper, we focus on the binarization methods as a core step in most image processing algorithms especially localization of the characters in scene images. We have developed in this paper our previous scheme which based on shape properties and geometric features to define text region and adopt our binarization scheme which based on Naïve Bayes classifier to convert grayscale image to binary image. Then we compare this binarization scheme with four famous different methods and explore their effects on detection characters in scene images. We found that our method outperforms the other four prior methods in detection characters with respect to Recall metric and the Otsu method follow our methods