Title :
Moving vehicle segmentation in a dynamic background using self-adaptive kalman background method
Author :
Ahmad, K.A. ; Saad, Z. ; Abdullah, Noramalina ; Hussain, Z. ; Noor, M. H Mohd
Author_Institution :
Fac. of Electr. Eng., Univ. of Technol. MARA, Malaysia
Abstract :
This paper introduce the adaptive kalman filter to modeling dynamic background for background subtraction. Background subtraction is a method to identify object and famous used in moving object segmentation. In this paper we also investigate a comparison study on Gaussian subtraction method, frame differencing method and approximate median method. The detection of object will be shown in the result.
Keywords :
Kalman filters; adaptive filters; image motion analysis; image segmentation; Gaussian subtraction method; adaptive Kalman filter; approximate median method; background subtraction; dynamic background; frame differencing method; moving object segmentation; moving vehicle segmentation; self-adaptive Kalman background method; Image segmentation; Kalman filters; Noise; Roads; Vehicle dynamics; Vehicles; Adaptive Kalman Background Subtraction Method; Frame Differencing Method; Mixture of Gaussian Method;
Conference_Titel :
Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on
Conference_Location :
Penang
Print_ISBN :
978-1-61284-414-5
DOI :
10.1109/CSPA.2011.5759918
