Special Issue Article
Restoring Degraded Documents by Using Neural Network - KSOM Based Hybrid Techniques
S.Nanthini and M.Yuvarani
Department of ECE, Erode Builder Educational Trust?s Group of Institutions, kangeyam, Tamil Nadu, India
|Related article at Pubmed, Scholar Google|
The objective of this paper is to specify a special problem in character recognition from document images where the verso side scripts appear as noise on front side. 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 in order to improve readability. We propose a new hybrid technique which is based on Neural Network Kohenen Self organizing Map (NNKSOM). The proposed method proves to perform processing techniques with improved performance. This method is absolutely useful for researchers engaged in recognizing any script worldwide as the same kind of distortion can be found in any image used worldwide.