Research on vehicle video image stabilization algorithm for mine
CHENG Deqiang
HUANG Xiaoli
LI Hang
WANG Haoyu
LI Shangtong
Abstract:For high error matching rate and poor real-time performance of global motion vector estimation caused by foreground moving target and high noise in video image captured by mine vehicle camera system,a vehicle video image stabilization algorithm for mine was proposed which was based on ORB feature matching and improved particle filter.In motion vector estimation stage,ORB algorithm is used to complete extraction of image feature points firstly.Then continuous three-frame difference method based on image block is adopted to quickly mark foreground movement area jointing space-time consistency criteria.Combined with foreground mark area,location of feature points is selected for the first time,and retained points are registered.Finally,affine transformation model is used to estimate motion vectors among frames.In motion filtering stage,a real-time particle filter algorithm based on estimation window is used to filter jitter components,and compensation parameters are obtained.The experimental results show that the proposed algorithm can effectively avoid influence of foreground moving target on image stabilization precision,and has quick processing speed.
Keywords:mine video monitoringvehicle videoimage stabilizationmotion vector estimationORB feature matchingparticle filter
Publication Date:2017-01-01
Online Publishing Date:2025-08-15(First online date of this platform, not the publication date of the document)
Pages:6( 21-26 )
Industry and Mine Automation

Industry and Mine Automation

PKUISTIC
ISSN:1671-251X
Year, Vol.(Issue):2017,43(11)