Image classification based on color and texture analysis

In this paper we propose a method to classify color images into different groups based on texture and color information. We take advantage of color information by clustering with a vector quantizer algorithm the color centroid of each image into the desired groups in the plane (V-1, V-2), the two chrominance components of the CIE Lab representation. To decrease the number of images misclassified, after that we apply a texture analysis to the images, specifically, we calculate the statistical parameters kurtosis and skewness. We apply the whole procedure to classify burn wound images. It was tested with 80 images, classifying without failure the 88.75% of them.