Application of K-Means clustering in hot spot detection for thermal infrared images

K-Means Clustering is one of the method for image segmentation which will subtract the interest area from background. By using K-Means Clustering, thermal image is divided into 2 layers which separates the hotter region from the background image. This will ease the hot spot detection on thermal infrared images. This paper presents work on the implementation of K-Means Clustering onto thermal images. The algorithm for thermal infrared image segmentation using K-Means Clustering was developed and executed using MATLAB R2015a software. It was proven that K-Means Clustering ease the hot spot detection from the thermal images.