Object detection using Metaheuristic algorithm for volley ball sports application

Object Detection has been a great challenge over the years. The reason behind is that, it is applied for numerous real time applications like vision based control, traffic control, video surveillance, sports analysis, etc. But, object detection in a video sequence is a highly challenging task. It has various problems like occlusion, fast moving objects, shadow, poor lighting, color contrast and other static background objects. This reason brought the object detection to be a thrust research area in the field of image processing. In the previous researches the conventional methods of object detection like Frame Difference, Mixture of Gaussian (MoG), Optical Flow etc., still have the above problems. Hence the research focuses on a different approach in object detection using Metaheuristic algorithm for the video sequence of volley ball player in the practice session. In this research three Metaheuristic Algorithms, namely Firefly, Teaching and Learning Based Optimization (TLBO) and Cuckoo Search Algorithm are used. These algorithms are evaluated and compared with the parameters like accuracy, precision, and recall. The result shows Cuckoo Search Algorithm is best suited to object detection especially in this application.