Efficient Binarization Technique for Handwritten Archive of South Dravidian Tulu Script

The segmentation of text from degraded document images is a challenging task comes under an image processing area with application of handwritten character recognition. Tulu is one of five major Dravidian language with many historical documents available in handwritten form. This paper presents an overview of Tulu script and adaptive image contrast based binarization technique for extracting text from a degraded background of Tulu paper document images. In this paper, we improve the quality of the text in the degraded document image using OTSU with several edge detection algorithms (i.e. canny, Sobel, and total variation) techniques applied to the degraded document image and Adaptive threshold with several edge detection algorithms (i.e. canny, Sobel, and total variation) techniques applied to the degraded document image. Finally, the qualities of these output images evaluated by PSNR and MSE. The best combination of threshold and edge detection techniques is selected by testing several degraded documents.