Shadows in images are crucial yet sometimes unwanted as they can decline results of computer vision algorithms. A shadow is caused by the interaction of light with objects in image surface. Shadows may lead to the failure of image analysis processes and also cause a poor quality of information which in turn leads to problems in implementation of algorithms. Shadow detection is the first step to shadow analysis and image processing in a number of applications. This paper presents a review of the existing literature in this area. An effort has been done to list some of the very crucial techniques related to shadow detection and removal. In the proposed method shadows are detected using difference index and succeeding thresholding. Many times, the shadow of the background information is merged with the foreground object and makes the process more complex. Once the shadows are detected it becomes simple to detect a non shadow area which is estimated using morphological operators.
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