An Adaptive DoubleThresholds Algorithm of Detecting Moving Objects

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An Adaptive DoubleThresholds Algorithm of Detecting Moving Objects

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[1]ZHANGZhen,LI Dan-dan.An Adaptive DoubleThresholds Algorithm of Detecting Moving Objects[J].Journal of Zhengzhou University (Engineering Science),2013,34(06):15-19.[doi:10.3969/j.issn.1671-6833.2013.06.004]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 34卷 Number of periods: 2013 06 Page number: 15-19 Column: Public date: 2013-12-30

Title:: An Adaptive DoubleThresholds Algorithm of Detecting Moving Objects

Author(s):: ZHANGZhen; LI Dan-dan; School of Electrical Engineering，Zhengzhou University，Zhengzhou 450001，China

Keywords:: double thresholds; motion object mask; functional chainneural network; moving object detection

CLC:: TP391.41

DOI:: 10.3969/j.issn.1671-6833.2013.06.004

Abstract:: Due to the environmental change of the noise，different weather conditions andillumination，which influence the results of movingobject detection，thispaperproposed an adaptive double thresholds motionobiect mask algorithm．Toimprove the rate of motive vehicle recognition，this novel method first used multiple’ frame average algorithm to initialize the background，and adopted functional chain neural network method to uDdate thetwoof high andlow thresholds dynamically，which can adjust to changeable illumination automatic‘ 1y．According to the motion mask algorithm，the region of the foreground and background wasidentified and the currentbackgroundwasupdated．Then the region of the foreground object could be attained by dynamic double thresholds background difference method．Combined with the mathematical morphology method，much shadowwasdeleted and the foregroundobject wasrecognized correctly．The experimental results demonstrated that this detectingalgorithmwasmore accurate and robust．

References:: [1]YANG Zhi-qi. A new algorithm of background imageextraction and update in the vehicle detection system[ C ]//2011 International Conference on MultimediaTechnology( ICMT )，Guangzhou，China:IEEEpress，2011 :5238 -5241.
[2]KIMA K，CHALIDABHONGEB T H，HARWOODAD，et al. Real-time foreground-background segmenta-tion using codebook model [J]. Real-Time Imaging，2005,3( 11):172 - 185.
[3]KORNPROBST P，DERICHE R，AUBERT G. Imagesequence analysis via partial difference equations [ J].Journal of Mathematical and Vision，1999，11 ( 1 ) :5- 26.

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