**6. Conclusion**

In this study, the statistical analysis of plantar temperature distribution based nonparametric way was done by using kernel density estimation. This approach showed the temperature distribution changes in different areas of the plantar region between the control and DM groups. The median and interquartile ranges are obtained from the statistical analysis. The extracted color features are grouped with the statistical measures of temperature distribution to automatically classify the data using SVM and KNN classifiers. Four different combinations of features sets were used to train and test the performance of the classifier. The SVM classier obtained better accuracy with Group 1 (RBT) feature sets.
