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基于单目视觉边缘频谱的散焦图像测距算法研究

介邓飞 王浩 吕惠芳 田波涛 张展翔

介邓飞, 王浩, 吕惠芳, 田波涛, 张展翔. 基于单目视觉边缘频谱的散焦图像测距算法研究[J]. 中国光学(中英文), 2023, 16(3): 627-636. doi: 10.37188/CO.2022-0171
引用本文: 介邓飞, 王浩, 吕惠芳, 田波涛, 张展翔. 基于单目视觉边缘频谱的散焦图像测距算法研究[J]. 中国光学(中英文), 2023, 16(3): 627-636. doi: 10.37188/CO.2022-0171
JIE Deng-fei, WANG Hao, LV Hui-fang, TIAN Bo-tao, ZHANG Zhan-xiang. An improved algorithm for monocular camera edge spectrum based ranging by defocused images[J]. Chinese Optics, 2023, 16(3): 627-636. doi: 10.37188/CO.2022-0171
Citation: JIE Deng-fei, WANG Hao, LV Hui-fang, TIAN Bo-tao, ZHANG Zhan-xiang. An improved algorithm for monocular camera edge spectrum based ranging by defocused images[J]. Chinese Optics, 2023, 16(3): 627-636. doi: 10.37188/CO.2022-0171

基于单目视觉边缘频谱的散焦图像测距算法研究

doi: 10.37188/CO.2022-0171
基金项目: 福建省自然科学基金面上项目(No. 2020J01577);福建省农业信息感知技术重点实验室项目(No. 2021ZDSYS0101)
详细信息
    作者简介:

    介邓飞(1982—),男,山西运城人,博士,副教授,硕士生导师,2014年于浙江大学获得博士学位,现为福建农林大学机电工程学院副教授,主要从事测控技术与智能装备方面的研究。E-mail:jiedengfei@163.com

  • 中图分类号: TP39;S24

An improved algorithm for monocular camera edge spectrum based ranging by defocused images

Funds: Supported by Fujian Provincial Natural Science Foundation Project (No. 2020J01577); the Fujian Key Laboratory of Agricultural Information Sensoring Technology (No. 2021ZDSYS0101)
More Information
  • 摘要:

    为了实现基于单目相机的弱或无表面纹理特征目标精确测距,提出了一种基于保留边缘频谱信息的改进散焦图像测距算法。通过对比以傅立叶变换和拉普拉斯变换为计算核心的两种经典散焦测距理论,构建相应的清晰度评价函数,根据灵敏度更好的频谱清晰度函数选择基于频谱的散焦测距法,并根据频谱清晰度函数在保留目标边缘信息的基础上选择频域计算范围,从而进行测距。为验证算法的可行性,本文采用6组不同的鸭蛋样本,获取不同光圈、不同距离的散焦图像,利用该改进算法求解鸭蛋到相机镜头的距离。实验结果表明,基于边缘频谱保留的散焦图像测距改进算法具有良好的测距效果,相关系数为0.986,均方根误差为11.39 mm,并发现对于斜放拍摄的鸭蛋图像进行图像旋转处理后,可有效地提升测距能力,均方根误差从11.39 mm下降至8.76 mm,平均相对误差从2.85%下降至2.28%,相关系数提升至0.99。基本满足了弱或无表面纹理特征目标测距的稳定、精度等要求。

     

  • 图 1  相机标定原理图

    Figure 1.  Schematic diagram of camera calibration

    图 2  实验用鸭蛋样本

    Figure 2.  Experimental samples of duck eggs

    图 3  部分清晰度不同的鸭蛋图像

    Figure 3.  Images of duck eggs with different definitions

    图 4  (a)基于拉普拉斯算子及(b)基于频谱的清晰度变化

    Figure 4.  Sharpness changes based on (a) the Laplacian operator and (b) spectrum

    图 5  (a)与(e)为鸭蛋图像,(b)与(f)为原频谱图,(c)与(g)为边缘保留频率截取图,(d)与(h)为频率截取后的频谱图像对应的时域图像

    Figure 5.  (a) and (e) are egg images, (b) and (f) are original spectral images, (c) and (g) are frequency-intercepted spectral images, (d) and (h) are time-domain images corresponding to the spectral images after frequency interception

    图 6  (a)频率截取后的清晰度变化图;(b)原清晰度变化图

    Figure 6.  (a) The definition change curve after the frequency interception; (b) the change of original definition

    图 7  基于边缘保留散焦图像测距算法流程图

    Figure 7.  The flow chart of ranging algorithm based on edge retaining defocus image

    图 8  实际距离与计算距离相关系数图

    Figure 8.  The correlations between observed distance and calculated distance

    图 9  图像旋转示意图。(a)原图;(b)旋转后图像

    Figure 9.  The process of image rotation. (a) Original image; (b) rotated image

    图 10  斜放鸭蛋经旋转处理后实际距离与计算距离相关系数图

    Figure 10.  The correlation between observed distance and calculated distance for oblique duck eggs after rotation treatment

    图 11  4号鸭蛋10组照片清晰度变化图

    Figure 11.  Clarity change of group 10 of egg No. 4

    图 12  4号鸭蛋取自然对数清晰度与物距关系图

    Figure 12.  Relationship between natural logarithmic clarity and object distance of egg No. 4

    图 13  拟合模型计算物距的相对误差

    Figure 13.  The relative error of the object distance from fitting model

    表  1  实际距离与计算距离实验结果

    Table  1.   The results of observed distance and calculated distance

    序号鸭蛋特征最大误差
    (mm)
    均方根误差
    (mm)
    平均相对
    误差(%)
    1绿壳、竖放10.906.591.63
    2白壳、竖放16.6010.222.87
    3白壳、竖放16.9910.652.98
    4白壳、横放13.928.302.24
    5白壳、斜放29.4416.934.31
    6绿壳、斜放24.7512.733.08
    总计29.4411.392.85
    下载: 导出CSV

    表  2  图像旋转前后测距结果对比

    Table  2.   The ranging results before and after image rotating

    序号处理方式最大误差
    (mm)
    均方根误差
    (mm)
    平均相对
    误差(%)
    5原始图像29.4416.934.31
    图像旋转后13.558.722.25
    6原始图像24.7512.733.08
    图像旋转后14.825.931.73
    总计原始图像29.4411.392.85
    图像旋转后16.998.762.28
    下载: 导出CSV

    表  3  拟合模型所得结果

    Table  3.   The results of fitting model

    序号实际距离/mm计算距离/mm误差/mm相对误差/%
    1250246.82−3.18−1.27
    2270273.413.411.26
    3290285.12−4.88−1.68
    4310310.620.620.20
    5330332.272.270.69
    6350354.304.301.23
    7370372.322.320.63
    8390390.980.980.25
    9410409.52−0.48−0.12
    10430424.64−5.36−1.25
    下载: 导出CSV

    表  4  拟合模型参数表

    Table  4.   Parameters of fitting model

    αβSSER2RMSE
    −91.97 (−96.21,−87.74)1349 (1302,1395)104.90.99683.62
    下载: 导出CSV
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  • 收稿日期:  2022-07-23
  • 修回日期:  2022-09-06
  • 录用日期:  2022-12-24
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