Abstract

AbstractThree dimensional range data provides useful information for computer vision, computer graphics, and object recognition applications. For these, extracting the range data reliably is utmost important. Therefore, various range scanners based on different operating principles are proposed in the literature. Although these scanners can be used in diverse applications, most of them cannot be used to scan shiny objects under ambient light. This is a severe restriction. We propose color invariant based binary and ternary coded structured light range scanners to solve this problem. We hypothesize that, by using color invariants we can eliminate the effects of highlights and ambient light in the scanning process. Therefore, we can extract the range data of shiny and matte objects in a robust manner. We implemented three different range scanners to test our hypothesis. We performed tests on various objects and provided their range data.KeywordsTest ObjectRange DataAmbient LightRange ScannerProjection PatternThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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