Improving shadow suppression in moving object detection with HSV color information
Year: 2002
Type: conference-paper
Abstract: Video-surveillance and traffic analysis systems can be heavily improved using vision-based techniques able 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 for moving visual object detection and tracking. The major novelty of the shadow detection technique is the analysis carried out in the HSV color space to improve the accuracy in detecting shadows. Signal processing and optic motivations of the approach proposed are described. The integration and exploitation of the shadow detection module into the system are outlined and experimental results are shown and evaluated.
Institutions: University of Modena and Reggio Emilia, University of Ferrara
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2138187652