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Survey Paper | Computer Science & Engineering | India | Volume 2 Issue 1, January 2013

Offline Handwritten Character Recognition Techniques using Neural Network: A Review

Vijay Laxmi Sahu | Babita Kubde ^[3]

Abstract: This paper presents detailed review in the field of Off-line Handwritten Character Recognition. Various methods are analyzed that have been proposed to realize the core of character recognition in an optical character recognition system. The recognition of handwriting can, however, still is considered an open research problem due to its substantial variation in appearance. Even though, sufficient studies have performed from history to this era, paper describes the techniques for converting textual content from a paper document into machine readable form. Offline handwritten character recognition is a process where the computer understands automatically the image of handwritten script. This material serves as a guide and update for readers working in the Character Recognition area. Selection of a relevant feature extraction method is probably the single most important factor in achieving high recognition performance with much better accuracy in character recognition systems.

Keywords: Neural Network, Feature extraction, Segmentation and Training, Classification

Edition: Volume 2 Issue 1, January 2013,

Pages: 87 - 94

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