Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/SpecialIssue.2013.030102
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Selected Papers from International Conference & Workshop On Advance Computing 2013, 2013.
Abstract: 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.
Shailaja Surkutlawar and Prof. Ramesh Kulkarni, “Removal of False Negatives in Moving Object Detection Using RGB color space” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Selected Papers from International Conference & Workshop On Advance Computing 2013, 2013. http://dx.doi.org/10.14569/SpecialIssue.2013.030102