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Image classification based on color and texture analysis

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2 Author(s)
B. Acha ; Seville Univ., Spain ; C. Serrano

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 (V1 , V2), the two chrominance components of the CIE Lab representation. To decrease the number of images misclassified, we then 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 88.75% of them

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Image and Signal Processing and Analysis, 2000. IWISPA 2000. Proceedings of the First International Workshop on

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