Combining Contour Based Orientation and Curvature Features for Writer Recognition

Authors:
Imran Siddiqi;Nicole Vincent
Affiliations:
Laboratoire CRIP5 ---SIP, Paris Descartes University, France 75006;Laboratoire CRIP5 ---SIP, Paris Descartes University, France 75006
Venue:
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Year:
2009

Citing 0
Cited 2

Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features

Pattern Recognition
Offline text-independent writer identification using codebook and efficient code extraction methods

Image and Vision Computing

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Abstract

This paper presents an effective method for writer recognition in handwritten documents. We have introduced a set of features that are extracted from two different representations of the contours of handwritten images. These features mainly capture the orientation and curvature information at different levels of observation, first from the chain code sequence of the contours and then from a set of polygons approximating these contours. Two writings are then compared by computing the distances between their respective features. The system trained and tested on a data set of 650 writers exhibited promising results on writer identification and verification.