Document Examiner Feature Extraction: Thinned vs. Skeletonised Handwriting Images

This paper describes two approaches to approximation of handwriting strokes for use in writer identification. One approach is based on a thinning method and produces raster skeleton whereas the other approximates handwriting strokes by cubic splines and produces a vector skeleton. The vector skeleto...

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Bibliographic Details
Main Authors: Pervouchine, V., Leedham, G.
Format: Conference Proceeding
Language:English
Subjects:
Biometrics
Data mining
Design methodology
Error analysis
Feature extraction
Forensics
Forgery
Skeleton
Telephony
Writing
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Summary:This paper describes two approaches to approximation of handwriting strokes for use in writer identification. One approach is based on a thinning method and produces raster skeleton whereas the other approximates handwriting strokes by cubic splines and produces a vector skeleton. The vector skeletonisation method is designed to preserve the individual features that can distinguish one writer from another. Extraction of structural character-level features of handwriting is performed using both skeletonisation methods and the results are compared. Use of the vector skeletonisation method resulted in lower error rate during the feature extraction stage. It also enabled to extract more structural features and improved the accuracy of writer identification from 78% to 98% in the experiment with 100 samples of grapheme "th" collected from 20 writers.
ISSN:2159-3442
2159-3450
DOI:10.1109/TENCON.2005.301018