Markers Location Monitoring on Images from an Infrared Camera Using Optimal Fuzzy Inference System

Many problems concerning appropriate calibration besides camera placement are focused by various researchers during measurement operations while dealing with thermal imaging camera. For easy processing of video stream, it is greatly necessitated to correct camera on a stand yaw/pitch/roll angles by utilizing various algorithms. The task is regarded as an easy one for hot object besides obviously visible in the infrared. Heat exchange process is greatly necessitated for registering initiation from a cold object. Boundary markers set positioning is accomplished on the supervised object in addition it requires an algorithm for recognition. A fuzzy assessed spatial relations-based approach is exploited previously for visual markers set detection on a rotating steel cylinder. However, that fuzzy assessed spatial relations-based approach not producing enough detection accuracy. To mitigate the above-mentioned issue this work introduces Intelligent Water Drop Optimization based Fuzzy Inference System (IWD-FIS) on the basis of fuzzy-intrinsic shape aspects such as objects, during a source image, and also their reciprocal reference frame. In this work Otsu algorithm is used for background as well as foreground segmentation. And then Features Extraction and Object Labelling are performed. Markers detection is done by using Proposed IWT-FIS based on the extracted features. The rule conclusions, parameter optimization and Membership Function (MF) parameters are concentrated mainly through this IWD-FIS. A state-of-the-art optimization sequence for the different FIS parameters is recommended rather than presenting a new algorithm.