|Table of Contents|

Recognition method of moving target using Bayesian probability theory

《南京理工大学学报》（自然科学版）[ISSN:1005-9830/CN:32-1397/N]

Issue:
2013年01期
Page:
76-
Research Field:
Publishing date:

Info

Title:
Recognition method of moving target using Bayesian probability theory
Author(s):
Xu Jing; Wang Xiaofeng
ZNDY of Ministerial Key Laboratory,NUST,Nanjing 210094,China
Keywords:
moving targets; infrared image sequences; target recognition; Bayesian probability; robusticity
PACS:
TP391
DOI:
-
Abstract:
To recognize moving targets simply and efficiently in infrared image sequences,a novel target recognition method based on Bayesian probability theory is proposed.The target initial position in the original image frame is obtained using the correlation matching algorithm.According to the recognition properties of the target,the decision functions are established.The classification of the connected regions in the current frame is determined by calculating Bayesian probability.The pattern vector is updated after the new target is located in the current frame for the target recognition in the next frame,and the purpose of moving target recognition is achieved.Experimental results show that:according to the recognized properties and probability calculation,the method can recognize the moving target fast and effectively with low computational complexity,and also the algorithm used is suitable for embedded system complementation and has strong robusticity.

References:

[1]葛炜,曹东杰,郝宏旭.红外制导技术在精确打击武器中的应用[J].兵工学报,2010,31(Z2):117-121. Ge Wei,Cao Dongjie,Hao Hongxu.Application of IR control and guidance technology in precise attack weapons[J].Acta Armamentar Ⅱ,2010,31(Z2):117-121.
[2]齐敏,李大健,郝重阳.模式识别导论[M].北京:清华大学出版社,2009.
[3]丁莹,李文辉,范静涛,等.基于模糊积分特征的红外图像运动目标检测算法[J].吉林大学学报(工学版),2010,40(5):1330-1335. Ding Ying,Li Wenhui,Fan Jingtao,et al.Fuzzy integral feature based algorithm for moving infrared object detection[J].Journal of Jilin University(Engineering and Technology Edition),2010,40(5):1330-1335.
[4]吴刚,唐振民,程勇,等.灰度共生矩阵纹理特征的运动目标跟踪方法[J].南京理工大学学报,2010,34(4):459-463. Wu Gang,Tang Zhenmin,Cheng Yong,et al.Object tracking method based on gray level cooccurrence matrix texture characteristic[J].Journal of Nanjing University of Science and Technology,2010,34(4):459-463.
[5]Shaik J S,Iftekharuddin K M.Probabilistic detection and tracking of IR targets[A].Photonic Devices and Algorithms for Computing[C].Bellingham,USA:SPIE Press,2004:90-101.
[6]Shaik J S,Iftekharuddin K M.Detection and tracking of targets in infrared images using Bayesian techniques[J].Optics & Laser Technology,2009,41(6):832-842.
[7]Gonzalez R C,Woods R E.Digital image processing[M].3rd.Beijing:Publishing House of Electronics Industry,2010.
[8]郭晓松,李奕芃,郭君斌.贝叶斯目标跟踪方法的研究[J].计算机工程,2009,35(12):137-139. Guo Xiaosong,Li Yipeng,Guo Junbin.Research on Bayesian target tracking method[J].Computer Engineering,2009,35(12):137-139.

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Last Update: 2013-02-15