Title :
Application of SVM in Embedded Character Recognition System
Author :
Liyan, Tian ; Xiaoguang, Hu ; Peng, Fei
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
Abstract :
During the development of hand-held character recognition device, the conflict of limited resources and high demanding for real-time makes the traditional classification method fails to meet the requirements of both speed and recognition rate at the same time. Thus, Support Vector Machines (SVM) classification algorithm is applied to the Embedded Character Recognition System. The SVM theory for pattern recognition is introduced firstly. One against one method is used to solve the Multi-class classification problem, with Cross-validation to sort the optimal parameters. The algorithm is finally transplanted to the embedded platform based on ARM. Comparing with the RBF neural networks, the experiment shows that the use of SVM for character recognition brings faster speed and higher recognition rate and meets the system requirement perfectly.
Keywords :
character recognition; pattern classification; radial basis function networks; support vector machines; RBF neural networks; SVM theory; cross-validation; embedded character recognition system; pattern recognition; support vector machines classification algorithm; Cameras; Character recognition; Embedded system; Ground penetrating radar; Hardware; Image recognition; Neural networks; Pattern recognition; Support vector machine classification; Support vector machines; character recognition; embedded system; support vector machine;
Conference_Titel :
Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-2799-4
Electronic_ISBN :
978-1-4244-2800-7
DOI :
10.1109/ICIEA.2009.5138404
