Survey of Methods for Character Recognition

180 Abstract— Character recognition has long been a critical area of the Artificial Intelligence. Recognition is a trivial task for humans, but to make a computer program that does character recognition is extremely difficult. Recognizing patterns is just one of those things humans do well and computers don’t. The reasons for this are the many sources of variability, abstraction and absence of hard-and-fast rules that define the appearance of a visual character. Hence rules need to be heuristically deduced from samples. This paper provides a review for various available methods. Character recognition methods are listed under two main headlines. The “Offline” methods use the static image properties. The offline methods are further divided into four methods, which are Clustering, Feature Extraction, Pattern Matching and Artificial Neural Network. The online methods are subdivided into k-NN classifier and direction based algorithm. Thus, an appreciation is provided for the range of techniques available for character recognition. The methods are discussed in detail throughout the paper.

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