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Target detection and recognition technology is a popular research field in image information processing technology. How to maturely apply this technology to land battlefields with complex backgrounds is an urgent pain point to be resolved. This paper first introduces the main factors affecting the performance of target detection and recognition under complex background conditions of land battlefields and analyzes the complexity, diversity, and uncertainty of the target background of land battlefields. Then, it reviews the research status of target recognition algorithms. Furthermore, it expounds on the key technologies of target detection and recognition under complex backgrounds, including multispectral complex target detection, automatic target recognition, dim and small target detection, and multi-channel heterogeneous information fusion. Finally, this paper predicts the tendencies of target detection and recognition technology in land battlefields.
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目标探测识别技术是图像信息处理技术的热门研究领域，面向陆战场复杂背景条件的目标探测识别技术如何成熟应用更是该领域亟待解决的痛点问题。文章介绍了陆战场复杂背景条件下影响目标探测识别性能的主要因素；分析了陆战场目标背景的复杂性、多样性和不确定性；回顾了国内外目标识别技术的发展历程；阐述了陆战场复杂背景目标探测识别的关键技术，包括多波段复合探测技术、目标自主识别技术、弱小目标检测识别技术、多通道异构信息融合技术；展望了陆战场目标探测识别技术的发展趋势。
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崔得东，研究员，中国兵器科技带头人，国务院政府特殊津贴专家。主要研究方向为智能化弹药导引技术。担任国家重点型号项目副总设计师。获国家科学技术进步奖一等奖1项，国防科学技术进步奖二等奖、省部级科学技术进步奖二等奖4项。出版专著1部，发表论文10余篇，获授权国防发明专利11项、新型实用专利1项。电子信箱：dedocui@126.com。 |
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崔得东，研究员，中国兵器科技带头人，国务院政府特殊津贴专家。主要研究方向为智能化弹药导引技术。担任国家重点型号项目副总设计师。获国家科学技术进步奖一等奖1项，国防科学技术进步奖二等奖、省部级科学技术进步奖二等奖4项。出版专著1部，发表论文10余篇，获授权国防发明专利11项、新型实用专利1项。电子信箱：dedocui@126.com。
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崔得东，研究员，中国兵器科技带头人，国务院政府特殊津贴专家。主要研究方向为智能化弹药导引技术。担任国家重点型号项目副总设计师。获国家科学技术进步奖一等奖1项，国防科学技术进步奖二等奖、省部级科学技术进步奖二等奖4项。出版专著1部，发表论文10余篇，获授权国防发明专利11项、新型实用专利1项。电子信箱：dedocui@126.com。
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目标表征技术的发展里程碑 LBP：Local Binary Pattern，局部二值模式特征；Haar：Haar-like Features，哈尔特征；HOG：Histogram of Oriented Gradient，方向梯度直方图特征；DPM：Deformable Parts Model，部件可变模型。
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典型的基于深度学习的多波段图像融合模型结构, figureFileSmall=d1gkiUfZtENMd/7fLKsARw==, figureFileBig=OU4K/5sOy3MORjntxPM8oQ==, tableContent=null), ArticleFig(id=1241719001148092510, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1241718971045564728, language=EN, label=null, caption=null, figureFileSmall=Xf5f+wJbsCGloos31HAK4w==, figureFileBig=H69WQKpf/5MJaXoL9w38VA==, tableContent=null), ArticleFig(id=1241719001223589983, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1241718971045564728, language=CN, label=图5, caption=
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基于目标识别的战场态势感知模型, figureFileSmall=NlXJpV13spemXsvzhPYP3Q==, figureFileBig=An45dC9tEk6722qT7Gzw5g==, tableContent=null), ArticleFig(id=1241719001437499490, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1241718971045564728, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
| 特征 | 优点 | 缺点 | 适用范围 |
| LBP | 对光照不敏感；运算速度快 | 计算量大 | 模板匹配 |
| HOG | 忽略光照颜色影响；表征数据维数降低 | 描述子生成过程长，实时性差；难以处理遮挡问题；噪点敏感 | 目标探测 |
| SIFT | 旋转、尺度缩放、亮度不变性；抗遮挡 | 方向信息敏感 | 目标识别
目标分类 |
), ArticleFig(id=1241719001508802659, tenantId=1146029695717560320, journalId=1146032081894723586, articleId=1241718971045564728, language=CN, label=表1, caption=
典型的传统目标表征技术的优缺点
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| 特征 | 优点 | 缺点 | 适用范围 |
| LBP | 对光照不敏感；运算速度快 | 计算量大 | 模板匹配 |
| HOG | 忽略光照颜色影响；表征数据维数降低 | 描述子生成过程长，实时性差；难以处理遮挡问题；噪点敏感 | 目标探测 |
| SIFT | 旋转、尺度缩放、亮度不变性；抗遮挡 | 方向信息敏感 | 目标识别
目标分类 |
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