An Error Analysis of Structured Light Scanning of Biological Tissue

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This paper presents an error analysis and correction model for four structured light methods applied to three common types of biological tissue; skin, fat and muscle. Despite its many advantages, structured light is based on the assumption of direct reflection at the object surface only. This assumption is violated by most biological material e.g. human skin, which exhibits subsurface scattering. In this study, we find that in general, structured light scans of biological tissue deviate significantly from the ground truth. We show that a large portion of this error can be predicted with a simple, statistical linear model based on the scan geometry. As such, scans can be corrected without introducing any specially designed pattern strategy or hardware. We can effectively reduce the error in a structured light scanner applied to biological tissue by as much as factor of two or three.
Original languageEnglish
Title of host publicationImage Analysis
Publication date2017
ISBN (Print)978-3-319-59125-4
Publication statusPublished - 2017
Event20th Scandinavian Conference on Image Analysis - Tromsø, Norway
Duration: 12 Jun 201714 Jun 2017


Conference20th Scandinavian Conference on Image Analysis
SeriesLecture Notes in Computer Science
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • 3D reconstruction, Error modeling, Structured light

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