Principal Component Analysis with Mean and Entropy Values for Thermal Images Classification
نویسنده
چکیده
This paper is aimed to report the experiment in revealing the classification of randomized thermograms tabulated by the mean values and entropy values, with the thermal camera of Fluke as a tool for capturing images, after the mathematical method of measurement. Two statistical features namely mean and entropy combined with principal component analysis (PCA) have been applied in this research to classify the types of thermograms after the image preprocessing. The results show that the method is quite promising to distinguish the thermal images.
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