Abstract
In this paper, in view of the limited focusing depth of industrial microlens and the feature of clear focusing when microscopic sample imaging needs sequence images, the non contact measurement method of 3D surface morphology based on depth of field is studied. A series of images of different focusing depth are taken by industrial microlens, and a new algorithm of 3D shape recovery is proposed. The 3D surface image of the object is recovered from the image sequence by the combination of the image preprocessing, the focusing evaluation function and the image post-processing. Use Laplasse function which has high robustness and high precision as the test function to calculate the three-dimensional depth information, and Gauss filter to optimize the depth map. The experimental results of solder balls on printed circuit boards show that the algorithm proposed in this paper can effectively restore the 3D surface morphology of objects with smaller errors.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nayar, S.K.: Shape from focus system for rough surface. In: Proceedings of the Image Understanding Workshop, pp. 539–606 (1992)
Darrell, T., Wohn, K.: Pyramid based depth from focus. In: Proceedings of the Computer Vision and Pattern Recognition, pp. 504–509 (1988)
Nayar, S.K., Nakagawa, Y.: Shape from focus. IEEE Trans. Pattern Anal. Mach. Intell. 16, 824–831 (1994)
Xiong, Y., Shafer, S.A.: Depth from focusing and defocusing. In: Proceedings of the Computer Vision Pattern and Recognition, pp. 68–73 (1993)
Xiong, Y., Shafer, S.: Depth from focusing and defocusing. Technical Report CMU-RI-TR-93-07, The Robotics Institute, Carnegie Mellon University, pp. 1–28 (1993)
Helmli, F.S, Scherer, S.: Adaptive shape from focus with an error estimation in light microscopy. In: Proceedings of the 2nd International Symposium on Image and Signal Processing and Analysis, Pula, Croatia, pp. 188–193 (2001)
Blahusch, G., Eckstein, W., Steger, C.: Calibration of curvature of field for depth from focus. In: ISPRS Archives, vol. XXXIV, Part 3/W8, pp. 173–177. Munich, 17–19 September 2003
Yokota, A, Yoshida, T, Kashiyama, H., et al.: High-speed sensing system for depth estimation based on depth-from-focus. In: IEEE International Symposium on Circuits and Systems, ISCAS, vol. 1, pp. 564–567 (2005)
Ohba, K., Ortega, J.C.P., et al.: Implementation of real time micro VR Camera. IEEJ Trans. Sens. Micromach. 120(E6), 264–271 (2000)
Jesus, C, Ortega, P., Ohba, K., et al. Real-time VR camera system. In: Proceedings of the Fourth Asian Conference on Computer Vision, vol. 9, pp. 500–513 (2000)
Ohba, K., Ortega, J.C.P., Tanie, K., et al.: Microscopic vision system with all-in-focus and depth images. Mach. Vis. Appl. 15, 55–62 (2003)
Acknowledgement
This research was partially supported by the key research project of Ministry of science and technology (Grant No. 2017YFB1301503) and the National Nature Science Foundation of China (Grant No. 51575332).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhan, Q. (2019). The Research of Three-Dimensional Morphology Recovery of Image Sequence Based on Focusing Method. In: Wang, K., Wang, Y., Strandhagen, J., Yu, T. (eds) Advanced Manufacturing and Automation VIII. IWAMA 2018. Lecture Notes in Electrical Engineering, vol 484. Springer, Singapore. https://doi.org/10.1007/978-981-13-2375-1_43
Download citation
DOI: https://doi.org/10.1007/978-981-13-2375-1_43
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2374-4
Online ISBN: 978-981-13-2375-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)