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

  • Authors:

  • Imran Siddiqi;Nicole Vincent

  • Affiliations:

  • LIAPDE - SIP, University Paris Descartes, 45 Rue des Saint Pères, 75006 Paris, France and College of Telecommunication Engineering, MCS-NUST, Rawalpindi, Pakistan;LIAPDE - SIP, University Paris Descartes, 45 Rue des Saint Pères, 75006 Paris, France

  • Venue:
  • Pattern Recognition
  • Year:
  • 2010

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Abstract

We propose an effective method for automatic writer recognition from unconstrained handwritten text images. Our method relies on two different aspects of writing: the presence of redundant patterns in the writing and its visual attributes. Analyzing small writing fragments, we seek to extract the patterns that an individual employs frequently as he writes. We also exploit two important visual attributes of writing, orientation and curvature, by computing a set of features from writing samples at different levels of observation. Finally we combine the two facets of handwriting to characterize the writer of a handwritten sample. The proposed methodology evaluated on two different data sets exhibits promising results on writer identification and verification.