Character Recognition Based On Maximum Membership Principle
Available Online September 2013.
- 10.2991/icsecs-13.2013.62How to use a DOI?
- Character recognition; fuzzy sets; feature extraction; maximum membership principle
Text recognition is one of the key technologies in an intelligent system. By means of highly effective extraction of the 7 typical features of characters, we dramatically shorten the time spent on feature extraction in this research. Then we built a membership function based on multidimensional normal distribution by utilizing normalized eigenvalue; and finally, we applied maximum membership principle (MMP)-based recognition technology to character recognition. The result indicates that this approach has evidently reduced the time and complexity of calculation while it was still able to maintain high accuracy of recognition.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yu Liao PY - 2013/09 DA - 2013/09 TI - Character Recognition Based On Maximum Membership Principle BT - Proceedings of the 2013 International Conference on Software Engineering and Computer Science PB - Atlantis Press SP - 283 EP - 285 SN - 1951-6851 UR - https://doi.org/10.2991/icsecs-13.2013.62 DO - 10.2991/icsecs-13.2013.62 ID - Liao2013/09 ER -