Determining Object Motion by Digital Image Correlation Method with Camera-Array Composed Cameras of Normal Frame Rate

  • Chi-Hung HwangEmail author
  • Tzu-Yu Kuo
  • Wei-Chung Wang
Conference paper
Part of the Structural Integrity book series (STIN, volume 8)


In this study, a camera-array constructed by four regular CCD cameras which can provide 20 frames per second output is used for taking images and then analyzed by digital image correlation method to determine the motion route of an object. The object for tracking is prepared by spraying to form artificial random dots on the surface. The camera-array is first calibrated by using black-white chess board to align all image centers of cameras within 2 pixels. No special time-synchronization among cameras is implemented for camera-array, images are taken by a triggering signal and then analyzed by digital image correlation method to obtain whole filed displacement filed with respect to reference frame which is taken before object moved. The test object first is first moved horizontally and then vertical away from and back to the original with maximum 20 mm, the motion at different time interval is then calculated by averaging the displacement field evaluated by DIC. The motion-path determined by DIC matches well to the predefined route but with small zig zag noise can be found from the plot. The result reveals the proposed camera-array can improve temporal resolution and provide motion route, however, the reason for zig zag motion departure is given in the end of this paper which is helpful to improve the proposed method.


Digital image correlation Motion route Camera-array Frame rate 



This paper was supported in part by the Ministry of Science and Technology, Taiwan (Grant no. MOST-106-2221-E-492-013 and MOST-107-2221-E-492-012).

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Instrument Technology Research Center, NARLabsHsinchuTaiwan
  2. 2.Department of Power Mechanical EngineeringNational Tsing Hua UniversityHsinchuTaiwan

Personalised recommendations