DocumentCode
527407
Title
Sequential blind image extraction based on particle swarm optimization
Author
Chen, Lei ; Zhang, Liyi ; Guo, Yanju ; Liu, Ting ; Li, Qiang
Author_Institution
Sch. of Inf. Eng., Tianjin Univ. of Commerce, Tianjin, China
Volume
5
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
2697
Lastpage
2700
Abstract
A sequential blind image extraction method based on particle swarm optimization was proposed. Normalized fourth-order cumulant was used as cost function in the method and traditional gradient algorithm was replaced by particle swarm optimization algorithm for optimizing it. The extracted source image component was wiped off using deflation method and source images can be extracted sequentially. Simulation results show that source images can be effectively extracted from mixed images using this method. Then, a moving target detection method based on sequential blind image extraction method was proposed and the movement trajectory can be clearly observed from sequential images.
Keywords
feature extraction; higher order statistics; image motion analysis; object detection; particle swarm optimisation; cost function; deflation method; gradient algorithm; moving target detection method; normalized fourth-order cumulant; particle swarm optimization algorithm; sequential blind image extraction method; source image component extraction; Blind source separation; Independent component analysis; Object detection; Optimization; Particle swarm optimization; Signal processing algorithms; Trajectory; moving target detection; normalized fourth-order cumulant; particle swarm optimization; sequential blind extraction; sequential images;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5582560
Filename
5582560
Link To Document