A Generic Approach for the Vietnamese Handwritten and Speech Recognition Problems
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Detection of heart valve diseases by using fuzzy discrete hidden Markov model
Expert Systems with Applications: An International Journal
Hybrid fuzzy HMM system for Arabic connectionist speech recognition
ISPRA'06 Proceedings of the 5th WSEAS International Conference on Signal Processing, Robotics and Automation
Fuzzy qualitative human motion analysis
IEEE Transactions on Fuzzy Systems
Additive and nonadditive fuzzy hidden Markov models
IEEE Transactions on Fuzzy Systems
Classification and quantification of occlusion using hidden markov model
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
Off-line cursive script recognition: current advances, comparisons and remaining problems
Artificial Intelligence Review
Hi-index | 0.00 |
For part I see ibid. vol.8, no. 1 (2000). This paper presents an application of the generalized hidden Markov models to handwritten word recognition. The system represents a word image as an ordered list of observation vectors by encoding features computed from each column in the given word image. Word models are formed by concatenating the state chains of the constituent character hidden Markov models. The novel work presented includes the preprocessing, feature extraction, and the application of the generalized hidden Markov models to handwritten word recognition. Methods for training the classical and generalized (fuzzy) models are described. Experiments were performed on a standard data set of handwritten word images obtained from the US Post Office mail stream, which contains real-word samples of different styles and qualities