Real Time Burning Image Classification Using Support Vector Machine

Authors

  • T.S. Hai HCMC
  • L.M. Triet HCMC
  • L.H. Thai HCMC
  • N.T. Thuy University of Engineering and Technology, Ha Noi

DOI:

https://doi.org/10.4108/eai.6-7-2017.152760

Keywords:

burning image classification, Support Vector Machine (SVM), multi-colour channels

Abstract

Burning image classification is critical and attempted problems in medical image processing. This paper has proposed the real time image classification for burning image to automatically identify the degrees of burns in three levels: II, III, and IV. The proposed model uses the multi-colour channels extraction and binary based on adaptive threshold. The proposed model uses One-class Support Vector Machine instead of traditional Support Vector Machine (SVM) because of unbalanced degrees of burns images database. The classifying precision 77.78% shows the feasibility of our proposed model.

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Published

06-07-2017

How to Cite

1.
Hai T, Triet L, Thai L, Thuy N. Real Time Burning Image Classification Using Support Vector Machine. EAI Endorsed Trans Context Aware Syst App [Internet]. 2017 Jul. 6 [cited 2024 Nov. 21];4(12):e4. Available from: https://publications.eai.eu/index.php/casa/article/view/1965