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Flame image recognition of alumina rotary kiln by artificial neural network and support vector machine methods

  • Zhang Hong-liang  (张红亮)Email author
  • Zou Zhong  (邹 忠)
  • Li Jie  (李 劼)
  • Chen Xiang-tao  (陈湘涛)
Article

Abstract

Based on the Fourier transform, a new shape descriptor was proposed to represent the flame image. By employing the shape descriptor as the input, the flame image recognition was studied by the methods of the artificial neural network(ANN) and the support vector machine(SVM) respectively. And the recognition experiments were carried out by using flame image data sampled from an alumina rotary kiln to evaluate their effectiveness. The results show that the two recognition methods can achieve good results, which verify the effectiveness of the shape descriptor. The highest recognition rate is 88.83% for SVM and 87.38% for ANN, which means that the performance of the SVM is better than that of the ANN.

Key words

rotary kiln flame image image recognition shape descriptor artificial neural network support vector machine 

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Copyright information

© Published by: Central South University Press, Sole distributor outside Mainland China: Springer 2008

Authors and Affiliations

  • Zhang Hong-liang  (张红亮)
    • 1
    Email author
  • Zou Zhong  (邹 忠)
    • 1
  • Li Jie  (李 劼)
    • 1
  • Chen Xiang-tao  (陈湘涛)
    • 2
  1. 1.School of Metallurgical Science and EngineeringCentral South UniversityChangshaChina
  2. 2.School of Information Science and EngineeringCentral South UniversityChangshaChina

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