光电跟踪系统高精度模板匹配跟踪算法

吴浩; 张勇; 李欣; 佀明华; 王伟明

光电跟踪系统高精度模板匹配跟踪算法

吴浩¹,
张勇^2, ,,
李欣³,
佀明华³,
王伟明³

1.
陆军工程大学石家庄校区电子与光学工程系, 河北石家庄 050003
2.
中国人民解放军32181部队, 河北石家庄 050000
3.
石家庄铁道大学电气与电子工程学院, 河北石家庄 050043

基金项目:

国家自然科学基金 51305455

陆军装备部资助课题 ZS2014070140A12002

详细信息

作者简介:
吴浩（1993-），男，河北辛集人，硕士研究生，研究方向为光电检测与图像处理

通讯作者:
张勇（1974-），男，河北邢台人，博士，高级工程师，研究方向为光电检测与图形图像处理。E-mail：bit10701159@163.com

中图分类号: O439;TP391
计量
- 文章访问数: 130
- HTML全文浏览量: 23
- PDF下载量: 44
- 被引次数: 0
出版历程
- 收稿日期: 2018-06-20
- 修回日期: 2022-11-18
- 刊出日期: 2022-12-20

High-precision Template Matching Tracking Algorithm for Optoelectronic Tracking System

1.
Department of Electronic and Optical Engineering, Army Engineering University Shijiazhuang Campus, Shijiazhuang 050003, China
2.
32181 Unit of PLA, Shijiazhuang 050000, China
3.
Department of Electrical and Electronics Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China

摘要

摘要: 为实现在光电跟踪系统条件下的高精度测量并且满足复杂环境下高精度目标匹配，本文选用去均值归一化互相关匹配算法。为提高匹配速度以及跟踪实时性，利用和表法计算公式中图像求和、平方和图像匹配互相关来简化计算复杂度；采用小波分层金字塔法作为搜索策略，并将模板质心作为参考点进行十字形搜索，引入终止阈值减少误匹配点进一步提高搜索速度。为验证该算法的有效性，实验中将光电跟踪系统放置在二维转台上，调整转台利用该算法跟踪目标靶板。实验结果表明，目标脱靶量控制在3个像素以内，该算法在光电跟踪系统上可实现高精度稳定跟踪。
- 模板匹配 /
- 光电跟踪系统 /
- 归一化互相关匹配 /
- 和表法 /
- 小波金字塔
Abstract: To achieve high-precision measurements under the operating conditions of optoelectronic tracking systems and satisfy high-precision target matching in complex environments, in this study we adopted the average normalized cross-correlation algorithm. To improve the matching speed and real-time tracking, the computational complexity was simplified by using the sum table method to correlate the sum of images, squares, and the correlation of images. The wavelet pyramid method was used as the search strategy, and the center of the template was used as the reference point for cross-shaped search. A termination threshold was introduced, which reduced the number of mismatched points to increase the search speed. To verify the effectiveness of the algorithm, an optoelectronic tracking system was placed on a two-dimensional turntable in an experiment that used the algorithm to track a target. The experimental results show that the missed target was controlled within 3 pixels. The proposed algorithm can realize high-precision and stable tracking in optoelectronic tracking systems.
- image matching /
- optoelectronic tracking system /
- normalized cross correlation /
- sum-table scheme /
- wavelet pyramid

HTML全文

图 1 金字塔分层图像的互相关匹配结果

Figure 1. Cross-correlation matching results of pyramid images

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图 2 质心法

Figure 2. Centroid method

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图 3 直线检测法

Figure 3. Line detection method

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图 4 待测图像模板匹配相关度

Figure 4. Template matching correlation of image

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图 5 待测图像匹配相关度大于0.8

Figure 5. Image matching correlation is greater than 0.8

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图 6 跟踪算法流程

Figure 6. Flowchart of tracing algorithm

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图 7 实验装置示意图

Figure 7. Experimental setup

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图 8 跟踪结果图像

Figure 8. Tracking result of image

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图 9 图像质心坐标序列

Figure 9. Sequence of image centroid coordinate

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图 10 非合作目标跟踪图像

Figure 10. Tracking image of non-cooperative target

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图 11 非合作目标质心坐标序列

Figure 11. Sequence of non-cooperative target centroid coordinate

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表 1 计算复杂度对比

Table 1. Comparison of computational complexity

Image size: M×N Window size: m×n		The traditional method		The proposed method
Image size: M×N Window size: m×n		Addition/subtraction	Multiplication	Addition/subtraction	Multiplication
Construction of sum-tables	S₁	0	0	3×M×N	0
	S₂	0	0	3×M×N	M×N
	S₃	0	0	3×M×N	M×N
Calculation of NCC	∑∑	M×N×m×n	0	3×M×N	0
	∑∑f²	M×N×m×n	M×N×m×n	3×M×N	0
	∑∑f·r	M×N×m×n	M×N×m×n	3×M×N	0
Total		3×M×N×m×n	2×M×N×m×n	18×M×N	2×M×N

下载: 导出CSV

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