DocumentCode :
3107507
Title :
Statistical method-based evolvable character recognition system
Author :
Wang Jin ; Tang Bin-bin ; Piao Chang-hao ; Lei Gai-hui
Author_Institution :
Key Lab. of Network control & Intell. Instrum., Chongqing Univ. of Posts & Commun., Chongqing, China
fYear :
2009
fDate :
5-8 July 2009
Firstpage :
804
Lastpage :
808
Abstract :
A novel character recognition system is proposed in this paper. By using the virtual reconfigurable architecture-based evolvable hardware, a series of recognition systems are evolved. To improve the recognition accuracy of the proposed systems, a statistical pattern recognition-inspired methodology is introduced. The performance of the proposed method is evaluated on the recognition of characters with different levels of noise. The experimental results show that the proposed statistical pattern recognition-based scheme significantly outperforms the traditional approach in terms of character recognition accuracy. For 1-bit noise, the recognition accuracy is increased from 84.8% to 96.7%. For 5-bit noise, the proposed system achieves a recognition accuracy of 84%.
Keywords :
character recognition; reconfigurable architectures; statistical analysis; evolvable character recognition system; evolvable hardware; statistical pattern recognition-inspired methodology; virtual reconfigurable architecture; Artificial neural networks; Character recognition; Circuits; Field programmable gate arrays; Hardware; Industrial electronics; Noise level; Pattern recognition; Reconfigurable architectures; Statistical analysis; character recognition; evolvable hardware; statistical pattern recognition; virtual reconfigurable architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2009. ISIE 2009. IEEE International Symposium on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-4347-5
Electronic_ISBN :
978-1-4244-4349-9
Type :
conf
DOI :
10.1109/ISIE.2009.5213594
Filename :
5213594
Link To Document :
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