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吴福培, 黄耿楠, 刘宇豪, 叶玮琳, 李昇平. 365彩票官网老虎机[J]. 365赌球. doi: 10.37188/CO.2023-0082
引用本文: 吴福培, 黄耿楠, 刘宇豪, 叶玮琳, 李昇平. 365彩票官网老虎机[J]. 365赌球. doi: 10.37188/CO.2023-0082
WU Fu-pei, HUANG Geng-nan, LIU Yu-hao, YE Wei-lin, LI Sheng-ping. 365赌球app下载中心[J]. Chinese Optics. doi: 10.37188/CO.2023-0082
Citation: WU Fu-pei, HUANG Geng-nan, LIU Yu-hao, YE Wei-lin, LI Sheng-ping. 365赌球app下载中心[J]. Chinese Optics. doi: 10.37188/CO.2023-0082

365彩票官网老虎机

doi: 10.37188/CO.2023-0082

  • 汕头大学 工学院 机械工程系, 广东 汕头 515063

基金项目:国家自然科学基金（No. 61573233）；广东省自然科学基金（No. 2021A1515010661）；广东省普通高校重点领域专项（No. 2020ZDZX2005）
详细信息
    作者简介:

    吴福培（1980—），男，广西玉林人，博士，教授。 2009年毕业于华南理工大学机械工程专业，获博士学位，现就职于汕头大学机械工程系。主要研究方向：自动光学检测和3D测量。E-mail：[email protected]

    黄耿楠（1997—），男，广东揭阳人，硕士。 2023年毕业于汕头大学机械工程专业，获硕士学位，现就职于比亚迪有限公司，担任高级工程师。研究方向：双目视觉与三维测量。E-mail：[email protected]

    刘宇豪（1999—），男，重庆人，硕士研究生，主要研究方向：双目视觉与三维测量。E-mail：[email protected]

    叶玮琳（1984—），女，广东潮州人，副教授，博士，主要研究方向：光电传感技术。E-mail：[email protected]

    李昇平（1966—），男，湖南永州人，教授，博士，主要研究方向：自适应控制、机器视觉。E-mail： [email protected]

  • 中图分类号:TP391.4

365赌球app下载中心

  • Department of Mechanical Engineering, College of Engineering, Shantou University, Shantou, Guangdong 515063, China

Funds:Supported by
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  • 摘要:

    视差不连续区域和重复纹理区域的误匹配率高一直是影响双目立体匹配测量精度的主要问题，为此，论文提出一种基于多特征融合的立体匹配算法。首先在代价计算阶段，通过高斯加权法赋予邻域像素点的权值，从而优化绝对差之和（Sum of absolute differences，SAD）算法的计算精度，并基于Census变换改进二进制链码方式，将邻域内像素的平均灰度值与梯度图像的灰度均值相融合，进而建立左右图像对应点的判断依据并优化其编码长度；然后，构建基于十字交叉法与改进的引导滤波器相融合的聚合方法，从而实现视差值再分配以减低误匹配率；最后，论文通过赢家通吃（Winner Take All，WTA）算法获取初始视差，并采用左右一致性检测方法、亚像素法提高匹配精度，从而获取其最终的视差结果，进而建立365彩票官网老虎机。实验结果表明，在Middlebury数据集的测试中，所提算法的平均非遮挡区域和全部区域的误匹配率为分别为2.67%和5.69%，测量200−900 mm距离的平均误差小于2%；而实际三维测量的最大误差为1.5%。实验结果检验了论文所提算法的有效性和可靠性。

    Abstract:

    The high mismatch rate of the parallax discontinuity region and the repeated texture region has been a major issue affecting the measurement accuracy of binocular stereo matching. For these reasons, this paper proposes a stereo matching algorithm that utilize multi-feature fusion. Firstly, the weight of neighboring pixels is given using Gaussian weighting method, which optimizes the calculation accuracy of the Sum of Absolute Differences (SAD) algorithm. Based on the Census transformation, the binary chain code technique has been enhanced to fuse the average gray value of neighborhood pixels with the average gray value of gradient image, and then the judgment basis of the left and right image corresponding points is established, and the coding length is optimized. Secondly, an aggregation technique has been developed that combines the cross method and the improved guide filter to redistribute disparity values with the aim of minimizing error. Finally, the initial disparity is obtained by the Winner Take All (WTA) algorithm, and the final disparity results are obtained by the left-right consistency detection method, sub-pixel method, and then a stereo matching algorithm based on the multi-feature SAD Census transform is established. The experimental results show that the average error matching rate of the proposed algorithm is 4.18%, the average error of the 200−900 mm distance is less than 2%, and the maximum error of the actual 3D data measurement is 1.5%, all using the test of the Middlebury dataset. The experimental results verify the effectiveness of the proposed algorithm.

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  • 图 1 改进Census变换示意图

    Figure 1. Schematic diagram of improved Census transform

    图 2 自适应十字交叉域

    Figure 2. Adaptive crossing domain

    图 3 优化聚合路径示意图

    Figure 3. Diagram of optimized aggregation path

    图 4 三种代价计算方法的视差图

    Figure 4. Parallax maps of three cost calculation methods

    图 5 实验结果图

    Figure 5. Schematic diagram of experimental results

    图 6 不同算法的误匹配率

    Figure 6. Mismatch rate of different algorithms

    图 7 不同亮度下算法的实验结果

    Figure 7. Experimental results of algorithms at different brightness levels

    图 8 噪声干扰下算法的实验结果

    Figure 8. Experimental results of the algorithm under noise interference

    图 9 测距实验对比

    Figure 9. Comparison of distance measuring experiments

    图 10 样本视差结果图的边缘提取

    Figure 10. Edge extraction of sample parallax result maps

    图 11 量块视差图

    Figure 11. Gauge block parallax map

    表  1 实验参数设置

    Table  1. Experimental parameters settings

    Parameter Value Parameter Value
    б 2 λ 0.003
    τ 1 16 ε 0.001
    τ 2 4 ω 9×7
    L 1 30 β 1 0.6
    L 2 15 β 2 0.4
    δ 0 1
    下载: 导出CSV

    表  2 不同算法在非遮挡区域和全部区域的误匹配率

    Table  2. Mismatch rate of different algorithms in the non-occluded region and all regions %

    Algorithm
    Tsukuba
    Venus
    Teddy
    Cones    		 Avg
    Non all Disc Non all Disc Non all Disc Non all Disc Non all Disc
    GC-occ 1.19 2.01 6.24 1.64 2.19 6.75 11.20 17.40 19.80 5.36 12.40 13.00 4.84 8.50 11.45
    SemiGlob 3.26 3.96 12.80 1.00 1.57 11.30 6.02 12.20 16.30 3.06 9.75 8.90 3.34 6.87 12.32
    RTCensus 5.08 6.25 19.20 1.58 2.42 14.20 7.96 13.8 20.30 4.10 9.54 12.20 4.68 8.01 16.48
    HCA 1.31 2.47 0.94 0.11 0.23 0.24 4.23 9.45 3.67 5.64 11.59 4.30 2.83 5.94 2.29
    Cross-ScaleGF 2.38 2.85 8.40 1.13 1.98 9.26 7.05 14.9 16.80 3.32 11.00 7.99 3.47 7.68 10.61
    GradAdaptWgt 2.26 2.63 8.99 0.99 1.39 4.92 8.00 13.10 18.60 2.61 7.67 7.43 3.46 6.19 9.99
    Proposed 1.25 2.73 0.90 0.15 0.31 0.31 4.62 8.73 2.98 4.69 10.98 4.11 2.67 5.69 2.08
    下载: 导出CSV

    表  3 三维测距实验结果

    Table  3. Experimental results of three-dimensional measurement

    序号 实际距离/mm 测量距离/mm 距离误差/mm 距离误差率/%
    1 200 198.42 −1.58 0.79
    2 300 302.55 2.55 0.85
    3 400 403.76 3.76 0.94
    4 500 495.05 −4.95 0.99
    5 600 606.06 6.06 1.01
    6 700 707.56 7.56 1.08
    7 800 809.52 9.52 1.19
    8 900 912.24 12.24 1.36
    下载: 导出CSV

    表  4 测量样本实验结果

    Table  4. Sample experimental results

    样本序号 实际长度/mm 测量长度/mm 误差/mm 误差率/%
    1 20 19.9575 −0.0425 −0.21
    35 34.6144 −0.3856 −1.1
    2 35 35.1649 0.1649 −0.47
    50 49.9672 −0.0328 −0.06
    3 5 4.9439 −0.0561 −1.12
    15 14.7565 −0.2435 −1.62
    4 20 20.3541 0.3541 0.71
    30 29.5784 −0.4216 −1.41
    下载: 导出CSV

    表  5 厚度测量结果

    Table  5. Thickness measurement results

    序号 实际厚度/mm 测量厚度/mm 测量误差/mm 绝对误差率/%
    1 1.00 1.0105 0.0105 1.05
    2 1.10 1.1235 0.0235 2.13
    3 1.20 1.2335 0.0335 2.79
    4 1.50 1.5563 0.0563 3.75
    5 2.00 1.9346 −0.0654 3.27
    下载: 导出CSV
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