In last two decades, visual surveillance has attracted more and more researchers because of its tremendous application prospects. One of the most critical challenge today for police and authorities is the timely and accurate detection of suspicious objects, such as unattended luggage, illegally parked vehicles, suspicious persons, and the like in or near airports, train stations, government buildings and in general all crowded public places to avoid unpleasant and destructive events. Present surveillance systems are designed to assist humans. The images that are provided by the cameras need to be constantly monitored by the human in order to identify any activity that is amiss. Therefore there is a need for the development of innovative surveillance system which will be able to automatically detect potentially dangerous situations. Static object is defined as ¿a stationary object that is not present in previous scene but remains in one position for defined time period¿. If the object moves before the predefined period is over it is not considered as a threat. The work proposed here is for developing a robust algorithm to detect a static object in image sequences.