A COLOR TEXTURE ANALYSIS METHOD BASED ON A GRAVITATIONAL APPROACH FOR CLASSIFICATION OF THE PAP-SMEAR DATABASE

Classification of pap-smear cell images is a relevant and challenging medical problem. In order to contribute to the analysis of these images, we propose to compute complexity based features from each color channel of them. Moreover, we propose to use the gravitational method, a novel and very discriminative approach which improves our ability to extract descriptors from the images. We compared our approach with results obtained from other color texture analysis methods by using both accuracy and AUC, which are measurements of performance. The obtained results (89.64% for accuracy and 0.9086 for AUC) demonstrate that color texture classification using the gravitational model is a feasible approach for the classification of pap-smear images.