Perspective rectification of document images using fuzzy set and morphological operations

In this paper, we deal with the problem of document image rectification from image 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 in the resulting image makes it hard to properly identify the contents of the captured text using traditional optical character recognition (OCR) systems. We propose in this work a new technique, which is capable of removing perspective 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 stroke boundaries and tip points (SBTP), which are extracted from character strokes based on multiple fuzzy sets and morphological operators. The algorithm needs neither high-contrast document boundary (HDB) nor paragraph formatting (PF) information. Experimental results show that our rectification process is fast and robust.