Name
Abstract | ||
|---|---|---|
In this paper we present a verification module that has as input the output provided by a word recognizer which is based on the segmentation-recognition paradigm. The word recognizer models words as the concatenation of character hidden Markov models (HMMs) and it provides at the output a list with the Top N best word hypotheses, including their likelihoods and the segmentation points of the words into sub words, which ideally should be characters. The verification module uses the segmentation points provided by the word recognizer for each word hypothesis to extract different features from each sub word. A classifier based on a multilayer perceptron neural network assigns a character class (A-Z) and estimates the a posteriori probability to each sub word that make up a word. Further, both the character class and the a posteriori probabilities are combined with the original output of the word recognizer to re-rank the word hypothesis into the Top N list. Experimental results show that the verification module improves the Top 1 recognition rate in 3.9% for an 85,092-word recognition task. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICFHR.2010.14 | Frontiers in Handwriting Recognition |
Keywords | Field | DocType |
posteriori probability,top n list,verification module,unconstrained handwritten words,sub word,character class,word recognizer models word,word recognizer,segmentation point,character level,word hypothesis,top n best word,hidden markov model,image segmentation,feature extraction,neural network,probability,word recognition,verification,hidden markov models,artificial neural networks,handwriting recognition,databases,multilayer perceptron | Computer science,Handwriting recognition,Image segmentation,Concatenation,Artificial intelligence,Classifier (linguistics),Intelligent word recognition,Pattern recognition,Word recognition,Speech recognition,Feature extraction,Hidden Markov model,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-8353-2 | 1 | 0.36 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro L. Koerich | 1 | 525 | 39.59 |
| Alceu de S. Britto Jr. | 2 | 30 | 2.96 |
| Luiz S. Oliveira | 3 | 476 | 47.22 |