Unobtrusive silhouette extraction using multivariate analysis and shadow removal in RGB color model

Object extraction is the initial step for any image processing task, such as visual surveillance, object tracking and intelligent transport system. Apart from other techniques, such as biometric system, these methods do not require any physical contact with an individual and can be performed from a distance and, therefore, used severely. Although several object extraction methods are available, this paper proposes a simple method to extract an object from video sequence based on the correlation between color model components. As the use of a single threshold is not suitable to correctly segment the object from the background, we are using two thresholds. Experimental results prove that this method can work well in static as well as dynamic background having different illumination conditions. Moreover, segmentation has side effects like moving cast shadows and self shadow, both of which reduce accuracy. In this paper, we present an automatic shadow removal method to extract objects. The analytical comparison with other foreground extraction, shadow detection and removal algorithms and their results are also presented for better understanding. The proposed method extract silhouette without any pre or post processing step of shadow removal.