The rising need for automation of systems has effected the development of text detection and recognition from images to a large extent. Text recognition has a wide range of applications, each with scenario dependent challenges and complications. How can these challenges be mitigated? What image processing techniques can be applied to make the text in the image machine readable? How can text be localized and separated from non textual information? How can the text image be converted to digital text format? This paper attempts to answer these questions in chosen scenarios. The types of document images that we have surveyed include general documents such as newspapers, books and magazines, forms, scientific documents, unconstrained documents such as maps, architectural and engineering drawings, and scene images with textual information.
M. P. Nevetha and A. Baskar, “Applications of Text Detection and its Challenges: A Review”, in ACM International Conference Proceeding Series, ACM New York, NY, USA ©2015 , 2015, pp. 712-721.