[1]许敬,王晓锋.基于贝叶斯概率的运动目标识别方法[J].南京理工大学学报(自然科学版),2013,37(01):76.
 Xu Jing,Wang Xiaofeng.Recognition method of moving target using Bayesian probability theory[J].Journal of Nanjing University of Science and Technology,2013,37(01):76.
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基于贝叶斯概率的运动目标识别方法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
37卷
期数:
2013年01期
页码:
76
栏目:
出版日期:
2013-02-28

文章信息/Info

Title:
Recognition method of moving target using Bayesian probability theory
作者:
许敬王晓锋
南京理工大学 智能弹药技术国防重点学科实验室,江苏 南京 210094
Author(s):
Xu JingWang Xiaofeng
ZNDY of Ministerial Key Laboratory,NUST,Nanjing 210094,China
关键词:
运动目标红外图像序列目标识别贝叶斯概率鲁棒性
Keywords:
moving targetsinfrared image sequencestarget recognitionBayesian probabilityrobusticity
分类号:
TP391
摘要:
为了能够简单并且有效地识别红外图像序列中的运动目标,提出了一种新颖的基于贝叶斯概率计算的目标识别方法。在初始帧中利用相关算法实现对目标的初始定位,分析当前目标识别属性,建立判别函数。计算当前帧中连通区域的概率判断其为目标类或者背景类。对当前帧中的目标定位后,更新模式向量,用于下一帧中该类目标的识别。实验结果表明,该方法根据目标的识别属性,通过概率计算能够快速有效地识别运动目标,计算量小,所涉及的算法适于嵌入式系统实现,具有较好的鲁棒性。
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.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介:许敬(1984-),女,博士生,主要研究方向:成像引信探测与目标定位,Email:ruole@163.com。
更新日期/Last Update: 2013-02-15