Title :
Color moving object segmentation based on Mixture Gaussian Models
Author :
Yan, Aiyun ; Li, Jingjiao ; Wang, Jiao ; Jiao Wang
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
The segmentation of color images sequence is an important research field of image processing and pattern recognition. In view of the current complex environment, the detection result of moving objects using traditional methods is not satisfying, a background of diminishing method based on the improved Mixture Gaussian Model is proposed. We establish Mixture Gaussian Models for each channel in (R, G, B) color space and utilize difference between current flame and background flame to separate foreground object and background, and use Morphological opening and closing operating to restraint interference. The experimental results indicate that the moving object can be extracted effectively.
Keywords :
Gaussian processes; flames; image colour analysis; image motion analysis; image segmentation; image sequences; object detection; RGB color space; background flame; background object; color image sequence; color moving object segmentation; current flame; diminishing method; foreground object; image processing; mixture Gaussian model; moving object detection; pattern recognition; Adaptation model; Data models; Gaussian distribution; Image color analysis; Image segmentation; Object detection; Pixel; Background Subtraction; Mixture Gaussian Model; Moving Object Detection;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583641