Low-Cost 3D Scanning Using Computer Vision and Triangulation
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Faculty Advisor: Professor Joseph Talghader
Department: Electrical and Computer Engineering ECE
Fall 2025 UROP
This project presents the design and implementation of a low-cost 3D scanning system using laser triangulation and open-source computer vision tools. A Raspberry Piābased platform was used to capture and process laser line deformation as an object rotated on a motorized turntable, enabling relative depth estimation and point cloud generation. Perspective distortion in the camera image was corrected using a homography-based transformation to ensure consistent spatial measurements. The system successfully produced an unscaled but recognizable point cloud representation of scanned objects. Limitations in calibration, testing, and photogrammetry integration constrained overall accuracy but demonstrated the feasibility of low-cost structured-light scanning.
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This research was supported by the Undergraduate Research Opportunities Program (UROP).
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Wan, Alexander; Liang, Tianyi. (2025). Low-Cost 3D Scanning Using Computer Vision and Triangulation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/277669.
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