Real Time Burning Image Classification Using Support Vector Machine - Hai, T.S.; Triet, L.M.; Thai, L.H.; Thuy, N.T. (EAI Endorsed Transactions on Context-aware Systems and Applications, 2017)
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.
Keywords: burning image classification; Support Vector Machine (SVM); multi-colour channels