Name
Abstract | ||
|---|---|---|
This paper presents an overview of feature extraction techniques for unconstrained Arabic handwritten word recognition. Choosing a technique for extraction the features considers the most important factor in achieving high recognition rates in word or character recognition. Different techniques were designed to extract the features from the Arabic words. These techniques are presented and discussed in terms of invariant invariance properties |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ITNG.2009.222 | ITNG |
Keywords | Field | DocType |
feature extraction technique,invariant invariance property,different technique,important factor,comparative study,unconstrained arabic handwritten word,character recognition,feature extraction,arabic word,high recognition rate,hidden markov models,testing,handwriting recognition,application software,image segmentation,skeleton,image recognition,pixel | Invariant (physics),Computer science,Word recognition,Handwriting recognition,Image segmentation,Speech recognition,Feature extraction,Natural language processing,Artificial intelligence,Application software,Hidden Markov model,Intelligent word recognition | Conference |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jawad H AlKhateeb | 1 | 45 | 2.73 |
| Jinchang Ren | 2 | 1144 | 88.54 |
| Jianmin Jiang | 3 | 985 | 81.39 |
| Stan S. Ipson | 4 | 12 | 1.68 |