舰船科学技术2024,Vol.46Issue(12) :174-177.DOI:10.3404/j.issn.1672-7649.2024.12.031

基于特征融合的无人船目标识别系统设计

Design of unmanned ship target recognition system based on feature fusion

颜悦 游学军 吕太之
舰船科学技术2024,Vol.46Issue(12) :174-177.DOI:10.3404/j.issn.1672-7649.2024.12.031

基于特征融合的无人船目标识别系统设计

Design of unmanned ship target recognition system based on feature fusion

颜悦 1游学军 1吕太之1
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作者信息

  • 1. 江苏海事职业技术学院信息工程学院,江苏南京 211170
  • 折叠

摘要

通过特征融合可获取全面的目标特征信息,利于提升目标识别的稳定性,为此设计基于特征融合的无人船目标识别系统.利用无人船搭载红外热成像仪与可见光摄像头,采集目标红外与可见光图像;通过处理器和可编程逻辑控制器,设计特征提取模块,用于提取红外与可见光图像的无人船目标特征;特征融合模块利用典型相关分析理论,融合红外与可见光图像的无人船目标特征;目标识别模块通过径向基函数网络,结合特征融合结果,输出无人船目标识别结果.实验结果证明,该系统可有效采集无人船目标的红外与可见光图像,完成特征提取;该系统具备较优的特征融合效果,并精准实现无人船目标识别.

Abstract

Through feature fusion,comprehensive target feature information can be obtained,which is conducive to im-proving the stability of target recognition.Therefore,an unmanned ship target recognition system based on feature fusion is designed.Infrared and visible images of the target are collected by the unmanned ship equipped with infrared thermal im-ager and visible light camera.Based on the processor and programmable logic controller,a feature extraction module is de-signed to extract the target features of the unmanned ship in infrared and visible images.The feature fusion module uses the theory of canonical correlation analysis to fuse the target features of the unmanned ship in infrared and visible images.The target recognition module outputs the target recognition result of unmanned ship through radial basis function network and feature fusion result.Experiments show that the system can effectively collect infrared and visible images of unmanned ship targets and complete feature extraction.The system has better feature fusion effect and accurately realizes the target recogni-tion of unmanned ship.

关键词

特征融合/无人船/目标识别/可编程逻辑/典型相关分析

Key words

feature fusion/unmanned ship/target recognition/programmable logic/canonical correlation analysis

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基金项目

江苏省高等学校基础科学(自然科学)研究重大项目(23KJA580002)

2022江苏省"青蓝工程"优秀教学团队(苏教师函202229号)

出版年

2024
舰船科学技术
中国舰船研究院,中国船舶信息中心

舰船科学技术

CSTPCD北大核心
影响因子:0.373
ISSN:1672-7649
参考文献量6
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