An Edge Based Thresholding Method

Histogram based thresholding methods are mainstream methods in the binarization of document images. However many uncertain factors such as complex signal-dependent noise and variable background intensity, which are caused by non-uniform illumination, shadow, smear, smudge or low contrast make it very difficult to obtain proper threshold through the histograms of images. This is caused by the shapes of the histograms which are arbitrary instead of being bimodal. In this paper we will propose a new edge based thresholding algorithm which converts the histograms of noisy images into bimodal, then it is possible to efficiently extract objects especially texture information from noisy background.