Loading…
Complex character decomposition using deformable model
Despite the fact that Chinese characters are composed of radicals and Chinese people usually formulate their knowledge of Chinese characters as a combination of radicals, very few studies have focused on a character decomposition approach to recognition, i.e. recognizing a character by first extract...
Saved in:
Published in: | IEEE transactions on human-machine systems 2001-02, Vol.31 (1), p.126-132 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Despite the fact that Chinese characters are composed of radicals and Chinese people usually formulate their knowledge of Chinese characters as a combination of radicals, very few studies have focused on a character decomposition approach to recognition, i.e. recognizing a character by first extracting and recognizing its radicals. In this paper, such an approach is adopted, and the problem of how to extract radical sub-images from character images is addressed by proposing an algorithm based on a deformable model (DM). The application of a DM to complex character decomposition (and recognition) is a novel one, and concepts like goodness of character decomposition have been exploited to formulate appropriate energy terms and to devise cost-effective minimization schemes for the problem. The advantage of the character decomposition approach is demonstrated by feeding the extracted radical images to an existing structure-based Chinese character recognizer, the outputs of which are then combined to classify the input. Simulation results show that the performance of the existing system can be improved significantly when character decomposition is used. |
---|---|
ISSN: | 1094-6977 2168-2291 1558-2442 2168-2305 |
DOI: | 10.1109/5326.923276 |