Feature extraction methods for character recognition-A survey

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This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. 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, reconstructability and expected distortions and variability of the characters. The problem of choosing the appropriate feature extraction method for a given application is also discussed. 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.

论文关键词:Feature extraction,Optical character recognition,Character representation,Invariance,Reconstructability

论文评审过程:Received 19 January 1995, Revised 19 July 1995, Accepted 11 August 1995, Available online 7 June 2001.

论文官网地址:https://doi.org/10.1016/0031-3203(95)00118-2