Depth estimation method of surface of micropart in microassembly space based on microscopic vision tomographic scanning images

Dai-Hua Wang; Kan Wang; Lin-Sen Qiang

doi:10.1111/jmi.13010

Depth estimation method of surface of micropart in microassembly space based on microscopic vision tomographic scanning images

J Microsc. 2021 Aug;283(2):77-92. doi: 10.1111/jmi.13010. Epub 2021 Apr 27.

Authors

Dai-Hua Wang^{1

2}, Kan Wang², Lin-Sen Qiang²

Affiliations

¹ Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education of China, Chongqing University, Chongqing, China.
² Precision and Intelligence Laboratory, Department of Measurement and Control Technology and Instrument, Chongqing University, Chongqing, China.

PMID: 33792928
DOI: 10.1111/jmi.13010

Abstract

Three-dimensional (3D) morphology of microparts has an important influence on performance of microassembly system that mainly assembles microparts in millimetre and micron scale. Because 3D morphology of microparts cannot be accurately obtained by conventional microscopic vision system, a depth estimation method of surface of micropart in microassembly space based on microscopic vision tomographic scanning (MVTS) images is proposed in this paper. The proposed method uses the positions of pixels with the largest focus values in MVTS image to construct the isodepth contours of surface of micropart and obtains the depth values of micropart's surface at the positions of MVTS by assigning depth values to corresponding isodepth contours. The MVTS images are obtained by MVTS and pixels with the largest focus values in MVTS image are obtained by focus measurement of MVTS images of micropart in microassembly space. On these bases, 3D spatial interpolation method is applied to map depth value of space between adjacent isodepth contours and to obtain depth values of all surface of micropart. Simulation experiments are carried out to verify the proposed method by generating simulated MVTS image array from two simulation objects, and the influence parameters of the proposed method are analysed. In established experimental setup of microassembly that can realise MVTS, experimental verification for the proposed depth estimation method are carried out by using cone cavity and end jaws of microgripper. 3D morphologies of depth maps of cone cavity and end jaws of microgripper are registered with their respective CAD models using iterative nearest point registration algorithm to quantify accuracy of depth estimation. The research results show that 3D morphology of micropart can be obtained by the proposed method and has better accuracy than those by conventional shape from focus method. This method provides a new way to obtain the morphology of microparts and lays a foundation for improving the accuracy and efficiency of gripping, alignment and approaching microparts in microassembly systems.

Keywords: depth estimation; microassembly; microscopic vision tomographic scanning; shape from focus; spatial interpolation; three-dimensional morphology.