New protocol for leg ulcer tissue classification from colour images

Measurement of wound healing status is very important for monitoring progress in individual patients. Tissue classification is a vital step in the development of an automatic measurement system for wound healing assessment. We present a new tissue classification protocol using the RGB (Red, Green and Blue) histogram distributions of pixel values from wound color images. These three histogram distributions (extracted features) were used as three two-dimensional (2D) input signals for classification. This protocol has been carried out using the KNN classifier and results show that the proposed protocol provides an extremely competent practical method for the classification of wound tissues.