抽象的

Stroke and Contrast Enhancement of Degraded Document Image through Binarization

Vibhavi R.N., Vrushali Uttarwar

Text Segmentation from a degraded document images is a very difficult task as the document image might contain lot of variations between the foreground and the background part.Binarization is been into intense research during the last few years. Most of the developed algorithms depend on statistical methods and do not consider the nature of document images. However, recent developments call for more specialized binarization techniques. Adaptive image contrast is used as a binarization technique in this paper . The adaptive image contrast is a combination of the local image contrast and the local image gradient. It is also tolerant towards variations caused due to degradations.The proposed technique constructs an adaptive contrast for an input degraded document image. The contrast map is then binarized and combined with Canny’s edge map to identify the text stroke edge pixels. A local threshold is estimated based on the intensities of detected text stroke edge pixels within a local window and this threshold is used for segmentation purpose.. The proposed method is simple, robust, and involves minimum parameters.