HMM-based Offline Recognition of Handwritten Words Crossed Out with Different Kinds of Strokes

Likforman-Sulem, L. and Vinciarelli, A. (2008) HMM-based Offline Recognition of Handwritten Words Crossed Out with Different Kinds of Strokes. In: The 11th International Conference on Frontiers in Handwriting Recognition, Concordia University, Montréal, Québec, Canada, August 19-21, 2008,

Abstract

In this work, we investigate the recognition of words that have been crossed-out by the writers and are thus degraded. The degradation consists of one or more ink strokes that span the whole word length and simulate the signs that writers use to cross out the words. The simulated strokes are superimposed to the original clean word images. We considered two types of strokes: wave-trajectory strokes created with splines curves and line-trajectory strokes generated with the delta-lognormal model of rapid line movements. The experiments have been performed using a recognition system based on hidden Markov models and the results show that the performance decrease is moderate for single writer data and light strokes, but severe for multiple writer data.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Vinciarelli, Professor Alessandro
• Authors: Likforman-Sulem, L., and Vinciarelli, A.
• College/School: College of Science and Engineering > School of Computing Science

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