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Detection of specularity using color and multiple views

  • Sang Wook Lee
  • Ruzena Bajcsy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

This paper presents a model and an algorithm for the detection of specularities from Lambertian reflections using multiple color images from different viewing directions. The algorithm, called spectral differencing, is based on the Lambertian consistency that color image irradiance from Lambertian reflection at an object surface does not change depending on viewing directions, but color image irradiance from specular reflection or from a mixture of Lambertian and specular reflections does change. The spectral differencing is a pixelwise parallel algorithm, and it detects specularities by color differences between a small number of images without using any feature correspondence or image segmentation. Applicable objects include uniformly or nonuniformly colored dielectrics and metals, under extended and multiply colored scene illumination. Experimental results agree with the model, and the algorithm performs well within the limitations discussed.

Keywords

Image Segmentation Specular Reflection Spectral Difference Illumination Source Color Point 
These 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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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Sang Wook Lee
    • 1
  • Ruzena Bajcsy
    • 1
  1. 1.GRASP Laboratory Department of Computer and Information ScienceUniversity of PennsylvaniaPhiladelphiaUSA

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