Interactive Parts Model: An Application to Recognition of On-line Cursive Script

Part of Advances in Neural Information Processing Systems 13 (NIPS 2000)

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Authors

Predrag Neskovic, Philip Davis, Leon Cooper

Abstract

In this work, we introduce an Interactive Parts (IP) model as an alternative to Hidden Markov Models (HMMs). We tested both models on a database of on-line cursive script. We show that im(cid:173) plementations of HMMs and the IP model, in which all letters are assumed to have the same average width, give comparable results. However , in contrast to HMMs, the IP model can handle duration modeling without an increase in computational complexity.