Development of an efficient algorithm in object detection for static and dynamic image

The aim of this paper work is to implement an efficient methodology to detect the moving object for static and dynamic images. Moving Object Detection is the most challenging area in video surveillance. Its task is to detect the object of interest in video. The wide application of this is in field like security, criminology etc. Moving object detection are important initial steps in object recognition, context analysis and indexing processes for visual surveillance systems. It is a big challenge for researchers to make a decision on which Detection algorithm is more suitable for which situation and/or environment and to determine how accurately object Detection (real-time or non-real-time) is made. There is a variety of object Detection algorithms (i.e. methods) and publications on their performance comparison and evaluation via performance metrics. In this paper Object Detection process is applied for static and dynamic images. Here Performance of this Object Detection on various classes of test images is reviewed and the possible direction of future research is indicated.