Abstract

Writer identification is the process of identifying the writer of the document based on their handwriting. Recent advances in computational engineering, artificial intelligence, data mining, image processing, pattern recognition and machine learning have shown that it is possible to automate writer identification. This paper proposes a model for text-dependent writer identification based on English handwriting. Features are extracted from scanned images of handwritten words and trained using pattern classification algorithm namely support vector machine. It is observed that accuracy of proposed writer identification model with Polynomial kernel show 94. 27% accuracy.

References

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