Document Image Dewarping Based on Line Estimation for Visually Impaired,

Publication Type:

Conference Paper


P. Kakumanu, N. Bourbakis, J. Black, Panchanathan S


18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’06), Washington, DC, p.625-631 (2006)


In this paper, we present an image-text dewalping methodology based on robust estimation of text-lines. When a text-page is captured by a camera, it suffers the perspective distortions and the page curl. The non-linear distortion due to page-curl is inherently present, given the surface nature of the pages and the text-book. The state-ofthe- art OCR systems have a very low performance on recognizing such distorted text. To remove both these distortions and to produce a flattened view of the text, we use the cues present in the image-text, i.e., the text-lines on the surface of the page are straight. The methodology requires only a single camera captured image and does not require any calibration or any other arpensive hardware setups as in other methods. Experimental results on a set of documents show that the methodology produces visually pleasing output and also improves OCR accuracy.


John A. Black, Jr

John A. Black, Jr

Research Scientist

Dr. Sethuraman "Panch" Panchanathan

Dr. Sethuraman "Panch" Panchanathan

Director, National Science Foundation