Small moving target detection model based on improved mixed disturbance gauss model

作     者：Bai, Ting Tian, Jinwen Sun, Xiao 

作者机构：National Key Laboratory of Science and Technology on Multi-spectral Information Processing School of Automation Huazhong University of Science and Technology Wuhan430074 China 

出 版 物：《Telkomnika (Telecommunication Computing Electronics and Control)》 (Telkomnika Telecomun. Compt. Electr. Control)

年 卷 期：2016年第14卷第3A期

页      面：229-236页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

基　　金：The National Natural Science Foundation of China (NSFC) projects under Grant No.61273279 and the National Natural Science Foundation of China (NSFC) projects under Grant No.61273241 

主　　题：Target tracking 

摘      要：In order to obtain ideal moving target detection results, a kind of moving target detection algorithm of improved mixture Gaussian model is proposed in this paper on the basis of analyzing the deficiency of traditional Mixture Gaussian model. Firstly, in this algorithm, the update rate is increased to better adapt to the change of environment and the idea of pixel connected region is introduced to remove the noise, then the invariance property of chroma is adopted to avoid arising of shadow phenomenon;finally, simulation comparison experiment is used to test its performance. The experiment results show that this algorithm can generate reliable background image and accurately and completely detect the moving target to obtain more superior detection results of comparison algorithm, which can meet the practical application requirement of target tracking. © 2016 Universitas Ahmad Dahlan. All rights reserved.