DocumentCode
3285975
Title
Notice of Retraction
Traffic video image segmentation based on mixture of Gaussian model
Author
Long-hui Guo ; Liang He ; Huai-zhong Li
Author_Institution
Sch. of Phys. & Electron. Inf. Eng., Wenzhou Univ., Wenzhou, China
fYear
2011
fDate
15-17 April 2011
Firstpage
1872
Lastpage
1875
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Vehicle Segmentation algorithm make a effective segmentation as there is a certain contrast between foreground and background, in order to deal with effective segmentation problem,in the case of the low contrast between foreground and background, cased by inappropriate camera parameters set or cloudy day. Then present a method simulating the gray level value in area of interesting changes by using of mixture of Gaussian modeLand realizing vehicle segmentation, experimental results show that the proposed method have achieved the expected goal.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Vehicle Segmentation algorithm make a effective segmentation as there is a certain contrast between foreground and background, in order to deal with effective segmentation problem,in the case of the low contrast between foreground and background, cased by inappropriate camera parameters set or cloudy day. Then present a method simulating the gray level value in area of interesting changes by using of mixture of Gaussian modeLand realizing vehicle segmentation, experimental results show that the proposed method have achieved the expected goal.
Keywords
Gaussian processes; image segmentation; traffic engineering computing; video cameras; video surveillance; Gaussian mixture model; background; camera; foreground; gray level value; image segmentation; traffic video segmentation; Cameras; Classification algorithms; Gaussian distribution; Image edge detection; Image segmentation; Pixel; Vehicles; area of interesting; background abstraction; image segmentation; mixture of gaussian model;
fLanguage
English
Publisher
ieee
Conference_Titel
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-8036-4
Type
conf
DOI
10.1109/ICEICE.2011.5777894
Filename
5777894
Link To Document