[1]张铭钧,张丽,万媛媛.基于特征融合的水下目标识别方法[J].哈尔滨工程大学学报,2011,(09):1190-1195.[doi:doi:10.3969/j.issn.1007-7043.2011.09.017]
 ZHANG Mingjun,ZHANG Li,WAN Yuanyuan.Underwater target recognition based on feature fusion[J].hebgcdxxb,2011,(09):1190-1195.[doi:doi:10.3969/j.issn.1007-7043.2011.09.017]
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基于特征融合的水下目标识别方法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2011年09期
页码:
1190-1195
栏目:
出版日期:
2011-09-25

文章信息/Info

Title:
Underwater target recognition based on feature fusion
文章编号:
1006-7043(2011)09-1190-08
作者:
张铭钧 张丽 万媛媛
1.哈尔滨工程大学 水下智能机器人技术国防科技重点实验室,黑龙江哈尔滨150001; 2.哈尔滨工程大学机电工程学院,黑龙江哈尔滨150001
Author(s):
ZHANG Mingjun ZHANG Li WAN Yuanyuan
1.National Key Laboratory of Science and Technology on Autonomous Underwater Vehicle,Harbin Engineering University,Harbin 150001,China; 2.College of Mechanical and Electrical Engineering,Harbin Engineering University,Harbin 150001,China
关键词:
特征提取Hu氏不变矩纹理特征目标识别
分类号:
TP24
DOI:
doi:10.3969/j.issn.1007-7043.2011.09.017
文献标志码:
A
摘要:
针对传统Hu氏不变矩易受摄像头径向畸变影响造成水下目标识别率低的问题,提出一种基于改进的Hu氏不变矩提取形状特征的方法,该方法依据摄像头的径向畸变模型重新恢复目标像素坐标与其灰度值的映射关系,构造出新的具有平移、缩放和旋转不变形的形状特征向量.同时为消除形状特征向量信息间的冗余问题,根据相关向量线性组合不改变向量自身性质的特点,提出一种基于相似度量准则进行对形状特征向量降维处理的方法.最后针对直接组合向量使得各特征权重一致而造成的识别率低的问题,给出了一种线性加权求和进行形状特征和纹理特征融合的方法.水下目标识别实验结果表明,该识别方法能够克服水下图像失真、信息冗余等不利因素,有效提高水下目标识别准确率.

参考文献/References:

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备注/Memo

备注/Memo:
国防基础科研基金资助项目;黑龙江自然科学基金资助项目(QC2009C02)
更新日期/Last Update: 2011-10-08