Name
Title | ||
|---|---|---|
Legal Amount Recognition Based on the Segmentation Hypotheses for Bank Check Processing |
Abstract | ||
|---|---|---|
Abstract: A sophisticated methodology of legal amount recognition based on the word segmentation hypotheses is introduced for automatic bank check processing. Word segmentation hypotheses are derived according to the grapheme level segmentation results of legal amount. Novel hybrid schemes of HMM-MLP classifiers are also introduced for producing the ordered legal word recognition results with reliable decision values. These values can be used for obtaining an optimal word segmentation path of over-segmentation hypotheses as well as an efficient rejection criterion of word recognition result. Simulation was performed with CENPARMI bank check database and shows quite encouraging results. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/ICDAR.2001.953928 | ICDAR-1 |
Keywords | Field | DocType |
cenparmi bank check database,optimal word segmentation path,automatic bank check processing,legal amount recognition,hmm-mlp classifier,word recognition result,bank check processing,grapheme level segmentation result,legal word recognition result,word segmentation hypothesis,legal amount,segmentation hypotheses,probability,handwriting recognition,optical character recognition,word segmentation,image segmentation,hidden markov model,law,databases,engines,multilayer perceptron,testing,word recognition,hidden markov models,hmm | Cashier's check,Pattern recognition,Computer science,Segmentation,Word recognition,Optical character recognition,Handwriting recognition,Text segmentation,Image segmentation,Artificial intelligence,Hidden Markov model | Conference |
ISSN | ISBN | Citations |
1520-5363 | 0-7695-1263-1 | 9 |
PageRank | References | Authors |
0.52 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kye Kyung Kim | 1 | 78 | 7.74 |
| Jin-Ho Kim | 2 | 469 | 44.48 |
| Yun Koo Chung | 3 | 45 | 3.87 |
| Ching Y. Suen | 4 | 7569 | 1127.54 |