Name
Abstract | ||
|---|---|---|
Hidden Markov Models (HMMs) are now widely used for off-line handwriting recognition in many languages. As in speech recognition, they are usually built from shared, embedded HMMs at symbol level, where state-conditional probability density functions in each HMM are modeled with Gaussian mixtures. In contrast to speech recognition, however, it is unclear which kind of features should be used and, indeed, very different features sets are in use today. Among them, we have recently proposed to directly use columns of raw, binary image pixels, which are directly fed into embedded Bernoulli (mixture) HMMs, that is, embedded HMMs in which the emission probabilities are modeled with Bernoulli mixtures. The idea is to by-pass feature extraction and to ensure that no discriminative information is filtered out during feature extraction, which in some sense is integrated into the recognition model. In this work, column bit vectors are extended by means of a sliding window of adequate width to better capture image context at each horizontal position of the word image. Using these windowed Bernoulli mixture HMMs, good results are reported on the well-known IAM and RIMES databases of Latin script, and in particular, state-of-the-art results are provided on the IfN/ENIT database of Arabic handwritten words. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.patrec.2012.09.002 | Pattern Recognition Letters |
Keywords | Field | DocType |
handwriting word recognition,speech recognition,windowed bernoulli mixture hmms,embedded hmms,embedded bernoulli,windowed bernoulli hmms,word image,binary image pixel,bernoulli mixture,better capture image context,recognition model,off-line handwriting recognition,latin,sliding window,arabic | Sliding window protocol,Pattern recognition,Computer science,Word recognition,Binary image,Handwriting recognition,Feature extraction,Speech recognition,Artificial intelligence,Hidden Markov model,Discriminative model,Bernoulli's principle | Journal |
Volume | ISSN | Citations |
35, | 0167-8655 | 11 |
PageRank | References | Authors |
0.55 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrií Giménez | 1 | 13 | 0.94 |
| Ihab Khoury | 2 | 21 | 1.95 |
| Jesús Andrés-Ferrer | 3 | 73 | 7.52 |
| alfons juan | 4 | 572 | 61.45 |