Name
Abstract | ||
|---|---|---|
This paper describes a recognition system for online handwritten Tibetan characters using advanced techniques in character recognition. To eliminate noise points of handwriting trajectories, we introduce a de-noising approach by using dilation, erosion, thinning operators of the mathematical morphology. Selecting appropriate structuring elements, we can clear up large amounts of noises in the glyphs of the character. To enhance the recognition performance, we adopt three-stage classification strategy, where the top rank output classes by the baseline classifier are re-classified by similar character discrimination classifier. Experiments have been carried out on two databases MRG-OHTC and IIP-OHTC. Test results show the used recognition algorithm is effective and can be applied in pen-based mobile devices. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-36824-0_10 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Keywords | Field | DocType |
databases mrg-ohtc,baseline classifier,recognition system,character recognition,online handwritten tibetan character,appropriate structuring element,similar character discrimination classifier,used recognition algorithm,advanced technique,recognition performance | Glyph,Pattern recognition,Handwriting,Intelligent character recognition,Computer science,Mathematical morphology,Speech recognition,Mobile device,Artificial intelligence,Structuring,Classifier (linguistics),Intelligent word recognition | Conference |
Volume | Issue | ISSN |
7423 LNCS | null | 16113349 |
Citations | PageRank | References |
1 | 0.36 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Long-long Ma | 1 | 26 | 5.72 |
| Jian Wu | 2 | 130 | 7.37 |