
The paper presents a method for isolated off-line character recognition using radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of radon histograms at every projecting angle. Thanks to DTW, it avoids compressing feature matrix into a single vector which may miss information. Comparison has been made with the state-of-the-art of shape descriptors over several different character as well as numeral datasets from different scripts.
DTW., [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, DTW, Character Recognition, Radon Transform
DTW., [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, DTW, Character Recognition, Radon Transform
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 28 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
