AN ADAPTIVE LAYER-BASED LOCAL BINARIZATION TECHNIQUE FOR DEGRADED DOCUMENTS

This paper presents a new technique for adaptive binarization of degraded document images. The proposed technique focuses on degraded documents with various background patterns and noise. It involves a preprocessing local background estimation stage, which detects for each pixel that is considered as background one, a proper grayscale value. Then, the estimated background is used to produce a new enhanced image having uniform background layers and increased local contrast. That is, the new image is a combination of background and foreground layers. Foreground and background layers are then separated by using a new transformation which exploits efficiently, both grayscale and spatial information. The final binary document is obtained by combining all foreground layers. The proposed binarization technique has been extensively tested on numerous documents and successfully compared with other well-known binarization techniques. Experimental results, which are based on statistical, visual and OCR criteria, verify the effectiveness of the technique.