Title :
Effective and Efficient Moving Object Segmentation via an Innovative Statistical Approach
Author :
Cuzzocrea, Alfredo ; Mumolo, Enzo ; Moro, Alessandro ; Umeda, Kazunori
Author_Institution :
ICAR, Univ. of Calabria, Cosenza, Italy
Abstract :
This paper deals with the background maintenance problem and proposes a novel pixel-wise solution. The proposed background maintenance algorithm is histogram-based. The algorithm has the following main features: fast background initialization, high accuracy in describing the real background and fast reaction to sudden changes. The basic idea of our algorithm is that the pixels are updated only if a statistic measure on the intensity variations of each pixels is greater to an adaptive threshold, thus reducing the I/O channel occupation. Experimental results on dynamic scenes taken from a fixed camera show that the proposed algorithm produces background images with an improved quality with respect to classical pixel-wise algorithms.
Keywords :
image segmentation; statistical analysis; adaptive threshold; background images; background maintenance algorithm; dynamic scenes; fast background initialization; histogram; innovative statistical approach; moving object segmentation; pixel-wise algorithms; Adaptation models; Computational modeling; Heuristic algorithms; Histograms; Image color analysis; Image reconstruction; Maintenance engineering;
Conference_Titel :
Complex, Intelligent, and Software Intensive Systems (CISIS), 2015 Ninth International Conference on
Conference_Location :
Blumenau
Print_ISBN :
978-1-4799-8869-3
DOI :
10.1109/CISIS.2015.23