Paper Title
A Noval Approach For Overlapped Character Recogntiton

Gigantic research has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese and Arabic scripts and Indian languages in [1]. There is no much work done on Overlapped script recognition. Although different efficient methodologies of Character recognition are proposed, but very few research implemented on Overlapped script recognition. In this article implemented the latest methods of Overlapped character recognition. Segmentation of Overlapped characters has an extremely strenuous task due to the large variety of characters and their shape, their shape and intimacy arrival in the script. Normalization, binarization and thinning are the pre-processing techniques used for in handwritten character recognition. Finally, we used Support Vector Machine (SVM) for resulting feature vectors and obtain classification performance in the character recognition scheme in [12]. The implemented recognition scheme provided 93 percent accuracy on Overlapped English character databases respectively. Keywords— OCR, Image Processing, Techniques of Overlapped Character Recognition, Chain Code, SVM Classifier.