Mou-Yen Chen

Learn More
This paper describes a complete system for the recognition of unconstrained handwritten words using a continuous density variable duration hidden Markov model (CD-VDHMM). First, a new segmentation algorithm based on mathematical morphology is developed to translate the 2-D image into a 1-D sequence of subcharacter symbols. This sequence of symbols is(More)
A successful handwritten word recognition (HWR) system using Variable Duration Hidden Markov Model (VDHMM) and the PDHMM strategy is easy to implement. The central theme of this paper is to show that if the duration statistics are computed, it could be utilized to implement an MD-HMM approach for better experimental results. This paper also describes a(More)
  • 1