Foreground-Background Regions Guided Binarization of Camera-Captured Document Images

Binarization is an important preprocessing step in several document image processing tasks. Nowadays handheld camera devices are in widespread use, that allow fast and flexible document image capturing. But, they may produce degraded grayscale image, especially due to bad shading or non-uniform illumination. State-of-the-art binarization techniques, which are designed for scanned images, do not perform well on camera-captured documents. Furthermore, local adaptive binarization methods, like Niblack [1], Sauvola [2], etc, are sensitive to free parameter values, which are fixed for whole image. In this paper, we describe a novel binarization technique using ridges-guided local binarization method, in which appropriate free parameter value(s) is(are) selected for each pixel depending on the presence or absence of ridge(s) in the local neighborhood of a pixel. Our method gives a novel way of automatically selecting parameter values for local binarization method, this improves binarization results for both scanned and camera-captured document images relative to previous methods. Experimental results on a subset of CBDAR 2007 document image dewarping contest dataset show a decrease in OCR error rate using reported method with respect to other stat-of-the-art bianrization methods.