Title :
Evaluation of Different Strategies to Optimize an HMM-Based Character Recognition System
Author :
Santos, Murilo ; Ko, Albert ; Oliveira, Luis S. ; Sabourin, Robert ; Koerich, Alessandro L. ; Britto, Alceu S.
Author_Institution :
Pontificia Univ. Catolica do Parana (PUCPR), Curitiba, Brazil
Abstract :
Different strategies for combination of complementary features in an HMM-based method for handwritten character recognition are evaluated. In addition, a noise reduction method is proposed to deal with the negative impact of low probability symbols in the training database. New sequences of observations are generated based on the original ones, but considering a noise reduction process. The experimental results based on 52 classes of alphabetic characters and more than 23,000 samples have shown that the strategies proposed to optimize the HMM-based recognition method are very promising.
Keywords :
handwritten character recognition; hidden Markov models; image denoising; image sequences; probability; HMM-based handwritten character recognition system; alphabetic character; noise reduction method; observation sequence; optimization; probability symbol; Character recognition; Handwriting recognition; Hidden Markov models; Neural networks; Noise reduction; Optimization methods; Spatial databases; Stochastic processes; Text analysis; Text recognition; HMM-based method; character recognition;
Conference_Titel :
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-4500-4
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2009.230
