2017/06/08 by Daniel L. Lau, Yu Zhang, Lau, Daniel L. +3 · 1 citation
Computer Science · Earth and Planetary Sciences · Engineering · Mathematics · #3D Surveying and Cultural Heritage #Artificial intelligence #Binary data #Binary number #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Computer vision #FOS: Computer and information sciences #Image (mathematics) #Image warping #Materials science #Mathematics #Noise (video) #Optical measurement and interference techniques #Optics #Phase (matter) #Physics #Profilometer #Projector #Scanner #Set (abstract data type) #Structured light #Structured-light 3D scanner #Surface Roughness and Optical Measurements #Surface finish #cs.CV
paper · pdf · doi:10.48550/arxiv.1706.02698
published in arXiv (Cornell University) (Cornell University)
arxiv created 2017/06/08 · openalex publication_date 2017/06/08 · arxiv updated 2017/06/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Structured light illumination is an active 3-D scanning technique based on projecting/capturing a set of striped patterns and measuring the warping of the patterns as they reflect off a target object's surface. In the case of phase measuring profilometry (PMP), the projected patterns are composed of a rolling sinusoidal wave, but as a set of time-multiplexed patterns, PMP requires the target surface to remain motionless or for scanning to be performed at such high rates that any movement is small. But high speed scanning places a significant burden on the projector electronics to produce contone patterns inside of short exposure intervals. Binary patterns are, therefore, of great value, but converting contone patterns into binary comes with significant risk. As such, this paper introduces a contone-to-binary conversion algorithm for deriving binary patterns that best mimic their contone counterparts. Experimental results will show a greater than 3 times reduction in pattern noise over traditional halftoning procedures.