Title :
Document Image Dewarping Based on Line Estimation for Visually Impaired
Author :
Kakumanu, P. ; Bourbakis, N. ; Black, J. ; Panchanathan, S.
Author_Institution :
Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH
Abstract :
In this paper, we present an image-text dewarping methodology based on robust estimation of text-lines. When a text-page is captured by a camera, it suffers both from 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-of-the-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 expensive 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
Keywords :
document image processing; handicapped aids; optical character recognition; text analysis; document image dewarping; line estimation; optical character recognition; robust estimation; Calibration; Cameras; Computer science; Hardware; Nonlinear distortion; Optical character recognition software; Robustness; State estimation; Streaming media; Text recognition; Document Image Analysis; Page-curl Dewarping and Assistive Devices; Perspective Rectification;
Conference_Titel :
Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7695-2728-0
DOI :
10.1109/ICTAI.2006.52