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Classification Methods of Skin Burn Images


Affiliations
1 Dept. of E&C, Atria Institute of Technology, Bangalore, India
2 Dr. Ambedkar Institute of Technology, Bangalore, India
3 Manipal Dot ,Manipal, India
 

cIn this paper, methods to automatically detect and categorize the severity of skin burn images using various classification techniques are compared and presented. A database comprising of skin burn images belonging to patients of diverse ethnicity, gender and age are considered. First the images are preprocessed and then classified utilizing the pattern recognition techniques: Template Matching (TM), K nearest neighbor classifier (kNN) and Support Vector Machine (SVM). The classifier is trained for different skin burn grades using pre-labeled images and optimized for the features chosen. This algorithm developed, works as an automatic skin burn wound analyzer and aids in the diagnosis of burn victims.

Keywords

kNN, SVM
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  • Classification Methods of Skin Burn Images

Abstract Views: 365  |  PDF Views: 184

Authors

Malini Suvarna
Dept. of E&C, Atria Institute of Technology, Bangalore, India
Sivakumar
Dr. Ambedkar Institute of Technology, Bangalore, India
U. C. Niranjan
Manipal Dot ,Manipal, India

Abstract


cIn this paper, methods to automatically detect and categorize the severity of skin burn images using various classification techniques are compared and presented. A database comprising of skin burn images belonging to patients of diverse ethnicity, gender and age are considered. First the images are preprocessed and then classified utilizing the pattern recognition techniques: Template Matching (TM), K nearest neighbor classifier (kNN) and Support Vector Machine (SVM). The classifier is trained for different skin burn grades using pre-labeled images and optimized for the features chosen. This algorithm developed, works as an automatic skin burn wound analyzer and aids in the diagnosis of burn victims.

Keywords


kNN, SVM