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Lei Yang Jianchen Luo Xiaowei Song Menglong Li Pengwei Wen Zixiang Xiong 《Entropy (Basel, Switzerland)》2021,23(7)
A robust vehicle speed measurement system based on feature information fusion for vehicle multi-characteristic detection is proposed in this paper. A vehicle multi-characteristic dataset is constructed. With this dataset, seven CNN-based modern object detection algorithms are trained for vehicle multi-characteristic detection. The FPN-based YOLOv4 is selected as the best vehicle multi-characteristic detection algorithm, which applies feature information fusion of different scales with both rich high-level semantic information and detailed low-level location information. The YOLOv4 algorithm is improved by combing with the attention mechanism, in which the residual module in YOLOv4 is replaced by the ECA channel attention module with cross channel interaction. An improved ECA-YOLOv4 object detection algorithm based on both feature information fusion and cross channel interaction is proposed, which improves the performance of YOLOv4 for vehicle multi-characteristic detection and reduces the model parameter size and FLOPs as well. A multi-characteristic fused speed measurement system based on license plate, logo, and light is designed accordingly. The system performance is verified by experiments. The experimental results show that the speed measurement error rate of the proposed system meets the requirement of the China national standard GB/T 21555-2007 in which the speed measurement error rate should be less than 6%. The proposed system can efficiently enhance the vehicle speed measurement accuracy and effectively improve the vehicle speed measurement robustness. 相似文献
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基于改进梯度和自适应窗口的立体匹配算法 总被引:3,自引:0,他引:3
立体匹配技术是计算机视觉领域的研究热点,由于问题本身的病态性,一直没有得到很好地解决。针对现有局部立体匹配算法精度不高以及易受光照失真影响的问题,提出了一种基于改进梯度匹配代价和自适应窗口的匹配算法。在传统梯度向量仅包含幅度信息的基础上,引入相位信息,并对原始匹配代价进行变换,进一步消除异常值;利用图像结构和色彩信息构建自适应窗口进行代价聚合;提出了一种局部视差直方图的视差精化方法,获得了高精度的视差图。实验结果表明,所提算法在Middlebury测试平台上平均误匹配误差为6.1%,且对光照失真条件具有较高的稳健性。 相似文献
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基于灰度投影的数字近景摄影立体影像匹配 总被引:3,自引:0,他引:3
根据数字近景摄影测量的特点,针对建筑物三维建模的需要,提出了基于灰度投影的影像匹配算法。该算法将影像行、列两个方向上的一维灰度投影,拓展为行、列、主对角线和次对角线四个方向上的一维灰度投影,计算左右影像的四个一维投影向量间的相似性测度的加权平均值作为最后的匹配测度。利用相对定向线性变换(RLT)算法来确定同名核线,以改进的动态定界法来控制待匹配点序列中后续点沿核线匹配的搜索范围,以减少匹配的搜索空间并提高匹配的准确度。利用该算法对建筑物数字近景摄影影像进行了实验,结果表明该算法具有较高的匹配速度和匹配准确率。 相似文献
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一种新的基于子线段的立体匹配算法 总被引:1,自引:0,他引:1
立体匹配是计算机视觉领域中最活跃的研究主题之一。为了精确并更快速的进行同名点匹配,提出了一种基于小波变换的子线段匹配方法。该方法利用样条二进小波变换系数在不同尺度下的模极大点,能提供在不同尺度下信号急速变化点的位置信息,采用由粗到细的匹配策略匹配这些特征点,并由这些特征点两两相邻的点构建子线段。采用加速方法,快速匹配子线段两端点之间的点。这种方法较好地解决了匹配精度和匹配速度之间的平衡问题。采用该方法对篦冷机内水泥熟料高度进行测量,实验表明,该方法能较精确地得出水泥熟料料层的分布状况。 相似文献
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Xiaowei Song Gaoyang Li Lei Yang Luxiao Zhu Chunping Hou Zixiang Xiong 《Entropy (Basel, Switzerland)》2022,24(8)
With the development of convolutional neural networks, the effect of pedestrian detection has been greatly improved by deep learning models. However, the presence of pseudo pedestrians will lead to accuracy reduction in pedestrian detection. To solve the problem that the existing pedestrian detection algorithms cannot distinguish pseudo pedestrians from real pedestrians, a real and pseudo pedestrian detection method with CA-YOLOv5s based on stereo image fusion is proposed in this paper. Firstly, the two-view images of the pedestrian are captured by a binocular stereo camera. Then, a proposed CA-YOLOv5s pedestrian detection algorithm is used for the left-view and right-view images, respectively, to detect the respective pedestrian regions. Afterwards, the detected left-view and right-view pedestrian regions are matched to obtain the feature point set, and the 3D spatial coordinates of the feature point set are calculated with Zhengyou Zhang’s calibration method. Finally, the RANSAC plane-fitting algorithm is adopted to extract the 3D features of the feature point set, and the real and pseudo pedestrian detection is achieved by the trained SVM. The proposed real and pseudo pedestrian detection method with CA-YOLOv5s based on stereo image fusion effectively solves the pseudo pedestrian detection problem and efficiently improves the accuracy. Experimental results also show that for the dataset with real and pseudo pedestrians, the proposed method significantly outperforms other existing pedestrian detection algorithms in terms of accuracy and precision. 相似文献
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Lei Yang Xiaoyu Guo Xiaowei Song Deyuan Lu Wenjing Cai Zixiang Xiong 《Entropy (Basel, Switzerland)》2022,24(11)
This paper proposes an improved human-body-segmentation algorithm with attention-based feature fusion and a refined corner-based feature-point design with sub-pixel stereo matching for the anthropometric system. In the human-body-segmentation algorithm, four CBAMs are embedded in the four middle convolution layers of the backbone network (ResNet101) of PSPNet to achieve better feature fusion in space and channels, so as to improve accuracy. The common convolution in the residual blocks of ResNet101 is substituted by group convolution to reduce model parameters and computational cost, thereby optimizing efficiency. For the stereo-matching scheme, a corner-based feature point is designed to obtain the feature-point coordinates at sub-pixel level, so that precision is refined. A regional constraint is applied according to the characteristic of the checkerboard corner points, thereby reducing complexity. Experimental results demonstrated that the anthropometric system with the proposed CBAM-based human-body-segmentation algorithm and corner-based stereo-matching scheme can significantly outperform the state-of-the-art system in accuracy. It can also meet the national standards GB/T 2664-2017, GA 258-2009 and GB/T 2665-2017; and the textile industry standards FZ/T 73029-2019, FZ/T 73017-2014, FZ/T 73059-2017 and FZ/T 73022-2019. 相似文献
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针对双目水下图像匹配不满足空气中常规极线约束的问题,提出一种基于深度约束的半全局算法以实现水下稠密立体匹配.首先采用深度约束确定匹配过程的深度约束搜索区域.然后,基于深度约束区域将绝对差值和梯度计算推广到二维区域并进行加权融合.在深度约束区域内的搜索过程中,采用胜者为王的策略确定某一视差值下的最佳行差及最佳行差下的匹配代价,并将其作为能量函数的数据项应用于半全局算法中,进行匹配代价的聚合.最后采用抛物线拟合法得到亚像素级的稠密视差图.在水下图片上进行的稠密立体匹配结果表明:相较于其他半全局匹配算法,本文算法在极大提高运行速度的前提下,可以获得良好的水下稠密立体匹配效果. 相似文献
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基于改进的拉普拉斯金字塔变换的图像融合方法 总被引:9,自引:0,他引:9
介绍了传统的拉普拉斯变换存在的缺点以及改进的拉普拉斯变换的基本原理和重构方法,分析了新的重构算法能够在重构时抑制噪声的特点。提出了在图像融合过程中会引入噪声的问题,并通过实验分析了图像融合过程中引入的噪声情况。使用新的重构算法能够在图像重构过程中,而不是在系数处理过程中,有效抑制融合噪声。给出了基于改进的拉普拉斯变换方法进行图像融合的基本架构,并对变换系数的设置与融合过程的处理进行了详细的介绍。仿真实验的主客观性能比较表明,基于改进的拉普拉斯变换的图像融合方法比其它几种基于金字塔变换的融合效果要好得多。 相似文献
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粗糙集理论是处理不确定性问题的数学方法,本文提出了基于粗糙集与小波变换相结合的图像融合算法。该方法首先将粗糙集理论应用于图像滤波中,对含有椒盐噪声的图像进行粗糙中值滤波,然后对滤波后的图像进行小波融合。实验结果表明,粗糙中值滤波有较强的去噪能力,且较好地保持了图像的细节信息,在此基础上进行小波融合,使得融合结果图像具有良好的效果。 相似文献
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基于传统SIFT方法和图像像素加权平滑融合的思想,提出了一种改进SIFT特征点的图像拼接方法。该方法首先利用Canny边缘检测算法获得图像的边缘点坐标,通过和SIFT算法关键点坐标进行对比,去除不稳定响应点;其次通过K-L变换降低算法复杂度,对得到的匹配点对,使用RANSAC算法进行提纯,计算投影变换模型参数;最后使用渐入渐出的加权融合算法平滑图像,消除图像之间的拼接缝隙。该算法的可行性和有效性通过实验结果可以得到证明。 相似文献
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Jing Fang Xiaole Ma Jingjing Wang Kai Qin Shaohai Hu Yuefeng Zhao 《Entropy (Basel, Switzerland)》2021,23(4)
The unavoidable noise often present in synthetic aperture radar (SAR) images, such as speckle noise, negatively impacts the subsequent processing of SAR images. Further, it is not easy to find an appropriate application for SAR images, given that the human visual system is sensitive to color and SAR images are gray. As a result, a noisy SAR image fusion method based on nonlocal matching and generative adversarial networks is presented in this paper. A nonlocal matching method is applied to processing source images into similar block groups in the pre-processing step. Then, adversarial networks are employed to generate a final noise-free fused SAR image block, where the generator aims to generate a noise-free SAR image block with color information, and the discriminator tries to increase the spatial resolution of the generated image block. This step ensures that the fused image block contains high resolution and color information at the same time. Finally, a fused image can be obtained by aggregating all the image blocks. By extensive comparative experiments on the SEN1–2 datasets and source images, it can be found that the proposed method not only has better fusion results but is also robust to image noise, indicating the superiority of the proposed noisy SAR image fusion method over the state-of-the-art methods. 相似文献
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一种改进的红外图像归一化互相关匹配算法 总被引:3,自引:2,他引:1
分析了传统归一化互相关算法在红外空中目标匹配定位时失效的原因,提出一种改进的红外图像归一化互相关匹配算法.该方法将模板和匹配区域之间的纹理相关计算看作一个最优化问题,寻求使图像纹理相关匹配鲁棒性最好的相关基准值,用图像的相关基准函数替代传统方法中的区域均值部分,构造了一种适用于的红外目标匹配的归一化相关算法.实验结果表明,该相关匹配算法对模板中背景部分的变化和非均匀性亮度变化有良好的抗干扰能力,较好地解决了恶劣环境下红外对空目标跟踪中匹配定位出错的问题. 相似文献
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基于光学测棒的立体视觉坐标测量系统的研究 总被引:5,自引:2,他引:5
提出了一种基丁测量与校准功能合一的光学测棒的立体视觉坐标测最系统.采用光学测棒作为成像目标,通过任意放置的两台摄像机获取测棒上的发光特征点的图像实现被测物体三维坐标的测量,同时利用测量数据定期对两台摄像机外部方位参数进行校准.深入研究了两台摄像机内部参数和外部方位参数校准过程中的校准件和校准算法的设计,以及系统测量建模等关键技术,提出了相应的解决方案,减小了摄像机内外参数校准及测量模型对测量结果的影响,提高系统的测量精度.实验结果表明.该系统的最大测量误差为0.11 mm. 相似文献
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自适应参考图像的可见光与热红外彩色图像融合算法 总被引:1,自引:0,他引:1
可见光与红外热图像的彩色图像融合技术是现今国内外高性能夜视技术发展的重要方向之一,该技术有效提高了人们对目标的探测和场景理解能力。目前常用的色彩传递算法多属于基于单幅参考图像的全局色彩传递算法,彩色融合图像的色调受到参考图像的影响较大,在实际应用中难以保证对各类场景的适应性。针对常规YUV空间色彩传递彩色图像融合算法的环境适应性问题,通过对植物、城镇和海天三类典型场景的分类与统计,发现了典型场景在UV通道的均值和标准差具有的较为明显的分类特性,由此提出了一种基于UV通道均值和标准差的自适应参考图像构造方法,使得可见光与热红外彩色图像融合算法具有较常规算法更好的环境适应性,融合图像的色彩具有较好的自然感,且算法处理量较小,对现有实时硬件融合处理算法的运算速度影响不大,是一种环境适应性强的自然感彩色融合处理算法。 相似文献
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基于面向对象分类约束的融合方法研究 总被引:5,自引:0,他引:5
像素级融合方法中常出现色彩突变或色彩失真现象。通过分类信息对融合进行约束可以部分消除目标地物边界的这些现象。然而传统的基于像素分类的影像融合方法由于分类中的“椒盐效应”,导致融合效果受到一定的影响和限制。采用面向对象分类约束的方法对该融合方法进行改进。首先采用面向对象分类方法进行影像分类,解决了基于像素分类中的“椒盐效应”问题;其次将分类结果作为影像融合的约束条件,利用色度饱和度明度(HSV)变换进行融合;最后将该方法的结果与多种融合方法的结果进行定量比较,发现该方法除在目视上取得很好的增强效果外,在信息熵、方差等指标上也取得了很好的效果。 相似文献