激光与光电子学进展, 2020, 57 (10): 101002, 网络出版: 2020-05-08
基于多聚焦图像序列融合的筒状类工件内壁形貌重构方法 下载: 834次
Reconstruction Method for Inner Wall Morphology of Cylindrical Workpiece Based on Multi-Focus Image Sequence Fusion
图像处理 筒状类工件 全景视觉 卷积神经网络 多聚焦图像融合 全景图展开 image processing cylindrical workpiece panoramic vision convolutional neural network multi-focus image fusion panoramic expansion
摘要
针对筒状类工件内壁缺陷和形貌特征的检测需求,提出了基于深度学习与机器视觉相结合的筒状类工件内壁全景成像方法。该方法基于变焦距成像,获取筒状类工件内壁多聚焦图像序列,利用基于卷积神经网络的多聚焦图像融合算法,融合不同景深的内壁图像序列,获取全聚焦的内壁全景视图。根据视觉成像的透视变换原理,采用逆映射全景图像,改进了内壁形貌重构方法,获取柱面坐标系下的筒状类工件内壁形貌图像。实验结果表明,提出的形貌重构方法能够有效实现内壁质量的检测,且成像质量较高。
Abstract
To satisfactorily detect the defects and topography of the inner wall of a cylindrical workpiece, this paper proposes a panoramic imaging method based on depth learning and machine vision. Through zoom imaging, this method obtains a multi-focus image sequence of the inner wall of a cylindrical workpiece, and uses a multi-focus image fusion algorithm based on convolution neural network to fuse the inner wall image sequences collected at different depths of field to get a fully focused panoramic view of inner wall. Based on perspective transformation principle of visual imaging, the inverse mapping panoramic mapping is used to improve the inner wall topography reconstruction method and obtain the inner wall topography image of the cylindrical workpiece under a cylindrical coordinate system. Experimental results show that the proposed topography reconstruction method can effectively detect the state of the inner wall, and the imaging quality is optimal.
王青青, 陈平. 基于多聚焦图像序列融合的筒状类工件内壁形貌重构方法[J]. 激光与光电子学进展, 2020, 57(10): 101002. Qingqing Wang, Ping Chen. Reconstruction Method for Inner Wall Morphology of Cylindrical Workpiece Based on Multi-Focus Image Sequence Fusion[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101002.