Abstract

The objective of this paper is to address a special problem in character recognition from document images were the reverse side scripts appear as noise on front side and even interfere with front side characters. Due to strong background artifacts so much of double-sided distortion is noticed in ancient documents. These are often caused by the so-called bleed-through effect. Even in well-preserved documents, a similar effect called show-through is noticed because of poor paper quality. These distortions must be removed to improve readability. We propose a new NNKSOM based hybrid technique, which incorporates statistical and diffusion model to deal with bleed-through grayscale document images. The proposed method proves to perform well regardless of the intensity differences between foreground and background. This is extremely useful for researchers engaged in recognizing the distorted documents in any script worldwide as the same kind of distortion can be found in most of the scripts used in the world.