Segmentation of burn images using the L*u*v* space and classification of their depths by color and texture imformation

Begona Acha Pinero; Carmen Serrano; Jose Ignacio Acha

doi:10.1117/12.467117

9 May 2002 Segmentation of burn images using the L*u*v* space and classification of their depths by color and texture imformation

Begona Acha Pinero, Carmen Serrano, Jose Ignacio Acha

Author Affiliations +

Proceedings Volume 4684, Medical Imaging 2002: Image Processing; (2002) https://doi.org/10.1117/12.467117
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

In this paper a burn color image segmentation and classification algorithm is proposed. The aim of the algorithm is to separate the burn wounds from healthy skin, and the different types of burns (burn depths) among themselves. We use digital color photographs. The system is based on the color and texture information, as these are the characteristics observed by physicians in order to give a diagnosis. We use a perceptually uniform color space (L^*u^*v^*), since Euclidean distances calculated in this space correspond to perceptually color differences. After the burn is segmented, some color and texture descriptors features are calculated and they are the inputs to a Fuzzy-ARTMAP neural network. The neural network classifies them into three types of burns: superficial dermal, depth dermal and full thickness. We get an average classification success rate of 88.89%.

Citation Download Citation

Begona Acha Pinero, Carmen Serrano, and Jose Ignacio Acha "Segmentation of burn images using the L*u*v* space and classification of their depths by color and texture imformation", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467117

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