Title | ||
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A Segment Extraction-Combination Algorithm Based on Polygonal Approximation and Finite State Machines for On-Line Chinese Character Recognition |
Abstract | ||
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In this paper, a segment extraction algorithm based on polygonal approximation for On-Line Chinese Characters Recognition (OLCCR) is presented. With this method, the point with the smallest interior angle is detected and the whole stroke is split into two adjacent curves by this point,which is called as a cut-off point or an inflexion. To each of the two curves, the same step is performed to detect the cut-off points respectively. The same operations are performed iteratively until the smallest interior angle in all the curves is larger than an appointed threshold value. All the cut-off points and the start-end points compose the stroke and every pair of adjacent points constructs a segment. After segments have been extracted, Finite State Machines is used to check whether the adjacent segments need combination thus redundant segments can be reduced. Experiments proved that this method has the advantages of less computing complexity and better approximating effect than other methods. An OLCCR system with this segment extraction and combination algorithm has achieved the speed of 20/s and the recognition rate of 97.2%. |
Year | DOI | Venue |
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2008 | 10.1109/ICYCS.2008.23 | ICYCS |
Keywords | Field | DocType |
segment extraction-combination algorithm,olccr system,on-line chinese character recognition,polygonal approximation,segment extraction algorithm,segment extraction,adjacent curve,redundant segment,adjacent segment,finite state machines,adjacent point,smallest interior angle,cut-off point,start-end point,interior angle,classification algorithms,computational complexity,image segmentation,finite element methods,stroke,approximation theory,approximation algorithms,feature extraction,data mining,finite state machine,automata | Approximation algorithm,Polygon,Pattern recognition,Approximation theory,Algorithm,Feature extraction,Finite element method,Image segmentation,Finite-state machine,Artificial intelligence,Statistical classification,Mathematics | Conference |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jing Chen | 1 | 0 | 0.34 |
Xinqiao Lu | 2 | 1 | 1.09 |
Qiaoling Luo | 3 | 1 | 0.75 |
Ping Li | 4 | 0 | 1.35 |
Xiaojuan Liu | 5 | 1 | 0.75 |