Enhanced Image Segmentation in Thermal Infrared Image Processing for Faulty Detection on Broadcasting Equipment

Evolution of electronics equipment evolves rapidly with the technologies invented. Broadcasting field also transform from analogue devices system into file-based system. As a continuously used equipment, the life-span is an important issue. To prevent breakdown, this broadcasting equipment must have a proper health inspection which provides an early detection for further action. This paper reports a faulty detection on broadcasting equipment with thermal infrared imaging system as a monitoring system. This study is carried out in the radio broadcasting studio which monitor the equipment through the operation time period. The data gathered from the system will undergo enhanced image segmentation method using k-means clustering with the implementation of histogram equalization for further image processing algorithm to detect the presence of hot spot. The final output image is compared with the number of hot spots detected for both images processed with implementation of histogram equalization and the image without the enhancement. Based from the result, it is shown that this proposed method successfully improved the results of the hot spot detection on thermal infrared images.