Document Image Dewarping Based on Text Line Detection and Surface Modeling

Document images produced by scanner or digital camera, usually suffer from geometric andphotometric distortions. Both of them deteriorate the performance of OCR systems. In this paper, wepresent a novel method to compensate for undesirable geometric distortions aiming to improve OCRresults. Our methodology is based on finding text lines by dynamic local connectivity map and thenapplying a low cost transformation to project curved area to 2-D rectangular area. We evaluate theperformance of the proposed methods in combination with four participating methods on the publicDFKI-I dataset (CBDAR 2007 dewarping contest), which contains camera-captured document images. Experimental results indicate the effectiveness and superiority of the proposed method.