基于r相关不均匀双线性插值策略的四目视觉圆柱周标拼接研究OA
Research on cylindrical circumferential label stitching based on four-eye vision with r-correlated uneven bilinear interpolation strategy
针对圆柱产品周标质检困难、误检率高等问题,该文提出一种基于四目视觉的圆柱周标稳定高质量拼接新方案.首先,为获取圆柱体真实位姿,给出了一种基于四准中心轴线的两层融合方法;然后,提出了一种 r 相关不均匀双线性插值的新颖策略,实现了对柱面标签图像高质量展开.在此基础上,通过归一化互相关(NCC)算法对柱面标签展开图中相邻2 幅图片进行特征匹配,并利用加权融合算法进行图像拼接融合.经实验验证,该文所提方案对不同半径的圆柱产品周标实时拼接时间小于 400 ms,满足工业生产对圆柱周标的准确性和稳定性检测要求.
Aiming at solving problems such as difficult quality inspection and high false detection rate of cylindrical product circumferential labels,a new scheme of stable and high-quality stitching of cylindrical circumferential labels based on four-eye vision is proposed.Firstly,a two-layer fusion method based on four quasi-central axes is given to obtain the real position of the cylinder.Then,a novel strategy of r-correlated uneven bilinear interpolation is employed to achieve high-quality unfolding of cylindrical label images.On this basis,the feature matching of two adjacent images in the cylindrical label unfolded image is performed by normalized cross-correlation(NCC)algorithm,and the weighted fusion algorithm is used for image stitching and fusion.The experiments demonstrate that the real-time stitching time of the proposed scheme is less than 400 ms for circumferential labels of cylindrical products with different radii,which meets the requirements of industrial production for the accuracy and stability detection of the cylindrical circumferential label.
李福东;蒋远雷;杨月全;蒋彬;黄强
扬州大学 信息与人工智能学院,江苏 扬州 225009扬州大学 信息与人工智能学院,江苏 扬州 225009扬州大学 信息与人工智能学院,江苏 扬州 225009扬州大学 信息与人工智能学院,江苏 扬州 225009扬州大学 信息与人工智能学院,江苏 扬州 225009
信息技术与安全科学
标签轴线融合不均匀插值图像拼接
labelaxis fusionuneven interpolationimage stitching
《南京理工大学学报(自然科学版)》 2026 (3)
253-262,10
国家自然科学基金(62073322)扬州市科技局国际科技合作项目(YZ2020200)教育部产学合作协同育人项目(201902321001)
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