Publication

Abstract : Hindi is the national language of India, spoken by more than 500 million people and is the second most popular spoken language in the world, after Chinese. Digital document imaging is gaining popularity for application to serve at libraries, government offices, banks etc. In this paper, we intend to provide a study on character binarization and segmentation of Hindi document images, which are the essential pre-processing steps in several applications like digitization of historically relevant books. In the case of historical documents, the document image may have stains, may not be readable, the background could be non-uniform and may be faded because of aging. In those cases the task of binarization and segmentation becomes challenging, and it affects the overall accuracy of the system. So these processes should be carried out accurately and efficiently. Here we experiment level set method in combination with diffusion techniques for improving the accuracy of segmentation in document process task.