Abstract
An adaptive block-based background modelling technique is proposed whereby the optimal number of model histograms is selected. The dynamic nature of a background tends to vary the pool of model histograms when capturing all possible scenes. Proposed is a novel method that recursively estimates the model weights, thereby continuously adjusting the number of histograms to robustly capture only the essence of intended objects. The proposed algorithm shows improved and reliable segmentation performance in various environments, including dynamic backgrounds with moving objects and repetitive variation of the pixel value.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
