Alphanumeric Character Recognition Based on BP Neural Network Classification and Combined Features
- DOI
- 10.1080/18756891.2013.816162How to use a DOI?
- Keywords
- Character Recognition, Combined Features, BP Network Classification, Euler Number
- Abstract
This paper puts forward a new method of alphanumeric character recognition based on BP neural network classification and combined features. This method firstly establishes three BP networks respectively for three categories of characters which are classified according to their Euler numbers, with the combination of grid feature and projection feature as the input of each BP network. When recognizing a character, its combined features are fed into the three BP networks simultaneously without the necessity for judging its Euler number. The final recognition result is elaborated by synthetically analyzing the outputs of three BP networks. Experimental results show that the proposed method can effectively improve the recognition ability and efficiency, and has a good property of fault tolerance and robustness. Furthermore, the weight coefficients of combined features for each BP network are optimized, which can further improve the recognition rate.
- Copyright
- © 2017, 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 - JOUR AU - Yong Luo AU - Shuwei Chen AU - Xiaojuan He AU - Xue Jia PY - 2013 DA - 2013/11/01 TI - Alphanumeric Character Recognition Based on BP Neural Network Classification and Combined Features JO - International Journal of Computational Intelligence Systems SP - 1108 EP - 1115 VL - 6 IS - 6 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.816162 DO - 10.1080/18756891.2013.816162 ID - Luo2013 ER -