A Comparative Approach for Standard Shadow Detection Methods

Abstract

False tracking is the biggest problem identified in tracking. The reasons for this is identified as shadow of the object to be tracked which have their shape mapping to the shape of the object. Dynamic shadow detection is the field in which videos are used. Dynamic shadow detection is found to be more exposed in literature due to the possibility of comparison, frame differentiation, background subtraction. All this not being possible in case of static images as they represent a single frame and are not used to that extent. Taking this as a challenge this paper presents static shadow detection in which the static shadow detection methods are mapped with dynamic images within the domain of image processing.The results so obtained are then authenticated from the user side. Every user may have different views, so as to bring the evaluation at a standard level this qualitative evaluation is quantified so as to be represented in form of tables and graphs for further analysis.