Résumé

Background subtraction is an essential step in the process of
monitoring videos. Several works have proposed models to dierentiate
the background pixels from the foreground pixels. Mixtures of Gaussian
(GMM) are among the most popular models for a such problem. However,
they suer from certain inconveniences related to the light variations
and complex scene due to the use of a xed number of Gaussians. In
this paper, we will propose an improvement of the GMM based on the
use of the bio-inspired algorithm AIRS (Articial Immune Recognition
System) to generate and introduce new Gaussian instead of using a
xed number of Gaussians. Our approach is to exploit the robustness
of the mutation function in the generation

Information

Item Type:	Conference
Divisions:
ePrint ID:	4430
Date Deposited:	2023-09-17
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/fr/publication/article/4430

BibTex