Automated handwriting analysis based on pattern recognition: a survey

Samsuryadi Samsuryadi, Rudi Kurniawan, Fatma Susilawati Mohamad


Handwriting analysis has wide scopes include recruitment, medical diagnosis, forensic, psychology, and human-computer interaction. Computerized handwriting analysis makes it easy to recognize human personality and can help graphologists to understand and identify it. The features of handwriting use as input to classify a person’s personality traits. This paper discusses a pattern recognition point of view, in which different stages are described. The stages of study are data collection and pre-processing technique, feature extraction with associated personality characteristics, and the classification model. Therefore, the purpose of this paper is to present a review of the methods and their achievements used in various stages of a pattern recognition system. 


Feature extraction; Pre-processing; Handwriting analysis; Personality trait; Pattern recognition

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