Document Image Dewarping Based on Line Estimation for Visually Impaired
P. Kakumanu, Nikolaos Bourbakis, John A. Black, Sethuraman Panchanathan · Proceedings - International Conference on Tools with Artificial Intelligence, TAI · 2006
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