In this paper, a novel heuristic based approach adopted from George.D.C.Calvacanti algorithm for removing background noise from all types of images with complex background is presented. In this approach Binarization is done by selecting two threshold values, one for foreground and another for background for the separation. Morphological techniques are used for improving the quality of the resultant image. In addition to this PSNR ratio is calculated for all the images and its variation with respect to the intensity of the background noise is observed.
Segmentation of touching hand written numerals and alphabets is a difficult task for recognizing individual characters. In this paper, the proposed algorithm is adopted from condego for the segmentation of hand written touching numerals, and is extended to segment the touching hand written English alphabets. The proposed method using Drop-fall algorithm is based on the moving of a marble on either side of the touching characters for selection of the point from where the cutting of the fused components should take palce. This method improvers the segmentation accuracy.
Abstract-Recognition of Indian language scripts is a challenging problem. Work for the development of complete OCR systems for Indian language scripts is still in infancy. Complete OCR systems have recently been developed for Devanagri and Bangla scripts. Research in the field of recognition of Telugu script faces major problems mainly related to the touching and overlapping of characters.
Segmentation of touchingTelugu characters is a difficult task for recognizing individual characters. In this paper, the proposed algorithm is for the segmentation of touching Hand written Telugu characters. The proposed method using Drop-fall algorithm is based on the moving of a marble on either side of the touching characters for selection of the point from where the cutting of the fused components should take place. This method improvers the segmentation accuracy higher than the existing one.
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