Title :
The research on video supervision technology based on mathematical morphology
Author :
Bin, Shao ; Yunliang, Jiang ; Zhen, Yang
Author_Institution :
Sch. of Inf. Eng., Zhejiang Univ., Huzhou, China
Abstract :
This paper studies some aspects needing to be improved in current video supervision technology. It puts forward video supervision background self-adaptive algorithm in complex environment, by using mathematical morphology, genetic algorithm, rough set theory, etc. We construct morphological structure element according with traffic moving target, and propose mathematical morphology analysis model for traffic video images. At the same time, we study feature extraction based on mathematical morphology and tracking detection methods, and establish typical violation pattern base by utilizing domain expert knowledge.
Keywords :
computer vision; feature extraction; genetic algorithms; knowledge based systems; mathematical morphology; object detection; road traffic; rough set theory; traffic engineering computing; video signal processing; domain expert knowledge; feature extraction; genetic algorithm; knowledge base system; mathematical morphology; road traffic video image; rough set theory; target detection; tracking detection method; video supervision background self-adaptive algorithm; Artificial intelligence; Cameras; Computerized monitoring; Educational institutions; Humans; Image analysis; Information analysis; Morphology; Target tracking; Traffic control; genetic algorithm; knowledge base; mathematical morphology; traffic supervision;
Conference_Titel :
Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3817-4
DOI :
10.1109/ICIMA.2009.5156559