Structural Features for Character Recognition System-A Review

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P.E. Ajmire
Rajeev Dharaskar,V M Thakare, S E Warkhede


This paper presents a review of structural features for character recognition. Structural features are the features that are physically a part of the structure of the character, such as straight lines, arcs, circles, intersections etc. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different representations of the characters, such as solid binary characters, character contours, skeletons (thinned characters) or gray-level subimages of each individual character. The feature extraction methods are discussed in terms of invariance properties, reconstruction ability, expected distortions and variability of the characters. When a few promising feature extraction methods have been identified, they need to be evaluated experimentally to find the best method for the given application. In this paper, we discuss the selection of appropriate standard structural features for character recognition


Keywords: Statistical features, Feature Extraction, character recognition.


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