DOCUMENT IMAGE RECTIFICATION USING FUZZY SETS AND MORPHOLOGICAL OPERATORS (WA-P7)

Author(s) : Shijian Lu (National University of Singapore, Singapore) Ben M. Chen (National University of Singapore, Singapore) C. C. Ko (National University of Singapore, Singapore)

Abstract : In this paper, we deal with the problem of document image rectification from images captured by digital cameras. The improvement on the resolution of digital camera sensors has brought more and more applications for non-contact text capture. Unfortunately, perspective distortion coupled with resulting images makes it harder to properly identify the contents of captured texts using the traditional optical character recognition (OCR) system. We propose in this work a new technique, which is capable of removing distortion and recovering the fronto-parallel view of text with a single image. Different from reported approaches in the literature, the image rectification is carried out using character boundary and tip point, which are extracted from character strokes based on multiple fuzzy sets and morphological operators. The algorithm needs neither camera calibration nor high-contrast document boundary. Experimental results show our rectification process is fast and robust.

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