Purdue University Graduate School
Liming_Chen_Dissertation_final.pdf (30.95 MB)

High-Speed, Large Depth-of-Field and Automated Microscopic 3D Imaging

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posted on 2024-04-22, 21:52 authored by Liming ChenLiming Chen

Over the last few decades, three-dimensional (3D) optical imaging and sensing techniques have attracted much attention from both academia and industries. Owing to its capability of gathering more information than conventional 2D imaging, it has been successfully adopted in many applications on the macro scale which ranges from sub-meters to meters such as entertainment, commercial electronics, manufacturing, and construction. For example, the iPhone “FaceID” sensor is used for facial recognition, and the Microsoft Kinect is used to track body motion in video games. With recent advances in many technical fields, such as semiconductor packaging, additive manufacturing, and micro-robots, there is an increasing need for microscopic 3D imaging, and several techniques including interferometry, confocal microscopy, focus variation, and structured light have been developed and adopted in these industries. Among these techniques, the structured light 3D imaging technique is considered one of the most promising techniques for in-situ metrology, owing to its advantage of simple configuration and high measurement speed. However, several challenges must be addressed in employing the structured-light 3D imaging technique in these fields.

The first challenge is the limited measurement range caused by the limited depth of field (DOF). Given the necessity for large magnification in the microscopic structured light system, the DOF becomes notably shallow, especially when pin-hole lenses are adopted. This issue is exacerbated by the fact that the measured objects in the aforementioned industries could contain miniaturized features spanning a broad height range. To address this problem, we introduce the idea of the focus stacking technique, wherein the focused pixels gathered from various focus settings are merged to form an all-in-focus image, into the structured-light 3D imaging. We further developed a computational framework that utilizes the phase information and fringe contrast of the projected fringe patterns to mitigate the influence of object textures.

The second challenge is the 3D imaging speed. The 3D measurement speed is a crucial factor for in-situ applications. We improved the large DOF 3D imaging speed by reducing the required fringe images from two aspects: 1) We developed a calibration method for multifocus pin-hole mode, which can eliminate the necessity of the 2D image alignment. The conventional method based on circle patterns will be affected during the feature extraction process by the significant camera defocusing. In contrast, our proposed method is more robust since it uses virtual features extracted from a reconstructed white flat surface under a pre-calibrated focus setting. 2)We developed a phase unwrapping method with the assistance of the electrically tunable lens (ETL), which is an optical component we used to capture fringe images under various focus settings. The proposed phase unwrapping method leverages the focal plane position of each focus setting to estimate a rough depth map for the geometric-constraint phase unwrapping algorithm. By doing this, the method eliminates the limitation on the effective working depth range and becomes feasible in large DOF 3D imaging.

Even with all previous methodologies, the efficiency of large DOF 3D imaging is still not high enough under certain circumstances. One of the major reasons is that we can still only use a series of pre-defined focus settings to run the focus stacking, since we have no prior on the measured objects. This issue could lead to low measurement efficiency when the depth range of the measured objects does not cover the whole enlarged DOF. To improve the performance of the system under such situations, we developed a method that introduces another computational imaging technique: the focal sweep technique, to help determine the optimal focus settings adapting to different measured objects.

In summary, this dissertation contributed to high-speed, large depth-of-field, and automated 3D imaging, which can be used in micro-scale applications from the following aspects: (1) enlarging the DOF of the microscopic 3D imaging using the focus stacking technique; (2) developing methods to improve the speed of large DOF microscopic 3D imaging; and (3) developing a method to improve the efficiency of the focus stacking under certain circumstances. These contributions can potentially enable the structured-light 3D imaging technique to be an alternative 3D microscopy approach for many academic studies and industry applications.


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Directorate for Computer & Information Science & Engineering

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Degree Type

  • Doctor of Philosophy


  • Mechanical Engineering

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Song Zhang

Additional Committee Member 2

David Cappelleri

Additional Committee Member 3

Shirley Dyke

Additional Committee Member 4

Fengqing Maggie Zhu

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