Name
Abstract | ||
|---|---|---|
This paper describes an optical recognition system for the handprinted Chinese characters. It is based on a novel string representation method and an inductive learning scheme that allows flexible (or elastic) representation and matching of unknown character instances. The system scans a character instance from four different views to obtain its peripheral segment information. A string representation is designed for representing the peripheral information at each of the four views. This representation can be generalized to represent the variations in different instances of a character by using an inductive learning algorithm. A clustering algorithm is developed to group the learned representation of characters into clusters in a hierarchical tree structure. Finally, a two-stage recognition process based on the developed representation is described. Experimental results demonstrate that high recognition rates can be obtained using the developed method. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1016/0020-0255(93)90082-W | Inf. Sci. |
Keywords | Field | DocType |
handprinted chinese character,string matching | String searching algorithm,Image processing,Tree structure,Artificial intelligence,Cluster analysis,Chinese characters,Recognition system,Pattern recognition,Unification,Speech recognition,String representation,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
67 | 1-2 | 0020-0255 |
Citations | PageRank | References |
1 | 0.36 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert I. Chou | 1 | 1 | 0.36 |
| Aaron Kershenbaum | 2 | 818 | 96.80 |
| Edward K. Wong | 3 | 268 | 24.19 |