Segmentation of thermal images using the fuzzy C-means algorithm

A segmentation methodology based on the fuzzy clustering algorithm is developed. The algorithm is utilized to segment a thermal image of occupants in a room taken by a thermoviewer. The purpose of segmentation is to identify the number and the positions of the occupants. Some useful applications can be realized, such as control of air-conditioning systems, security systems, and so on. The approach consists of two stages. The first stage is to distinguish occupants from a background in an image using the fuzzy C-means (FCM) algorithm. The authors have selected a suitable measure for determining the number of clusters and modified it for FCM. The purpose of the second stage is to distinguish each occupant by locating local temperature peaks in the image. A region-growing algorithm is introduced for more accurate segmentation based on the membership value determined by FCM and the number of located peaks. Some experimental results are included that relate to thermal images obtained in a meeting room