Removal of False Negatives in Moving Object Detection Using RGB color space
SHAILAJA SURKUTLAWAR SURKUTLAWAR, Prof. Ramesh · International Journal of Advanced Computer Science and Applications · 2013
Moving objects detection is a fundamental step in many vision based applications. Background subtraction is the typical method. Many background models have been introduced to deal with different problems. The method based on mixture of Gaussians is a good balance between accuracy and complexity, and is used frequently by many researchers. But it still cannot provide satisfied results in some cases. Video-surveillance and traffic analysis systems can be heavily improved using vision-based techniques to extract, manage and track objects in the scene. However, problems arise due to shadows. In particular, moving shadows can affect the correct localization, measurements and detection of moving objects. This work aims to present a technique for shadow detection and suppression used in a system using RGB color space for moving visual object detection and tracking. Experimental results show that the proposed approach can significantly enhance shadow suppression results and moving objects are detected.