Predicting the Identity of a Person using Aggregated Features of Handwriting
DOI:
https://doi.org/10.14738/aivp.31.997Keywords:
Classification, Feature Extraction, Prediction, Training, Writer Identification.Abstract
The identification of an individual based on handwriting is a useful biometric modality. The biometric modalities are broadly classified into two types, namely psychological and behavioral characteristics. The physiological characteristics are fingerprint, face, iris, retina, hand geometry and the behavioral characteristics are voice, signature, gait, handwriting. Handwriting recognition plays vital role in forensic analysis, signature verification and network security. The automatic writer identification will be a valuable and relevant tool in forensic analysis and biometric authentication. Hence it is proposed to design and develop a model for automatic recognition of a person based on handwriting using pattern recognition technique.
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