Zhu Xiao, Liu Zixiao, Zhang Xin, Sui Tingting, Li Ming
School of Electronic Information, Shanghai DianJi University, Shanghai 201306, China.
J Imaging. 2022 Oct 7;8(10):275. doi: 10.3390/jimaging8100275.
In the beverage, food and drug industry, more and more machine vision systems are being used for the defect detection of Polyethylene Terephthalate (PET) bottle caps. In this paper, in order to address the result of cylindrical distortions that influence the subsequent defect detection in the imaging process, a very fast image stitching algorithm is proposed to generate a panorama planar image of the surface of PET bottle caps. Firstly, the three-dimensional model of the bottle cap is established. Secondly, the relative poses among the four cameras and the bottle cap in the three-dimensional space are calculated to obtain the mapping relationship between three-dimensional points on the side surface of the bottle cap and image pixels taken by the camera. Finally, the side images of the bottle cap are unfolded and stitched to generate a planar image. The experimental results demonstrate that the proposed algorithm unfolds the side images of the bottle cap correctly and very fast. The average unfolding and stitching time for 1.6-megapixel color caps image can reach almost 123.6 ms.
在饮料、食品和药品行业，越来越多的机器视觉系统被用于聚对苯二甲酸乙二酯（PET）瓶盖的缺陷检测。本文针对成像过程中影响后续缺陷检测的柱面畸变问题，提出了一种非常快速的图像拼接算法，以生成PET瓶盖表面的全景平面图像。首先，建立瓶盖的三维模型。其次，计算四个相机与三维空间中瓶盖之间的相对位姿，以获得瓶盖侧面三维点与相机拍摄图像像素之间的映射关系。最后，将瓶盖的侧面图像展开并拼接以生成平面图像。实验结果表明，所提算法能够正确且快速地展开瓶盖的侧面图像。对于160万像素的彩色瓶盖图像，平均展开和拼接时间可达近123.6毫秒。
