Deterministic Fuzzy Approach for Tracking Motion Detection in Video Surveillance Using Image Processing Techniques - Mary Magdalene Viola W. (International Journal of Intelligent Systems and Applications in Engineering, 2023)
The process of object identification in images are generally observable content in image processing due to the immense popularity in image component analytics domain but each existence rely on its foundation theoretical objectives through its unique success rates. The object tracking in video surveillance CCTV or any video source system is a tedious process due to its random motion characteristics and frequent continuous parameter analysis for efficient tracking. The existing surveillance video object motion tracking approach methods fails in the areas of learning and pattern matching strategies along with proper computations and logical reasoning towards the next movement in the successive frames. The primary objective of this research is to incorporate 5 fundamental parameters for object tracking such as relative distance, direction change, speed approximation calculated time to reach the target and prediction of movement using fuzzy approach in the field of image processing. This research article proposes a deterministic fuzzy approach for tracking motion detection in video surveillance using image processing techniques for achieving those 5 fundamental parameters. In near future this research article focuses on the implementation of artificial intelligence based motion detection in video surveillance with augmented reality system.