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Proceedings Paper

Using color to segment images of 3-D scenes
Author(s): Glenn Healey
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Paper Abstract

Physical models for color image formation provide constraints which are useful for interpreting 3D scenes. I summarize the physics underlying color image formation. Models for surface and body reflection from metals and dielectrics are analyzed in detail. This analysis allows us to evaluate the benefits we stand to gain by using color information in machine vision. I show from the reflection models that color allows the computation of image statistics which are independent of scene geometry. This principle has been used to develop an efficient algorithm for segmenting images of 3D scenes using normalized color. The algorithm applies to images of a wide range of materials and surface textures and is useful for a wide variety of machine vision tasks including 3D recognition and 3D inspection. Experimental results are presented to demonstrate the scope of the models and the capabilities of the segmentation algorithm.

Paper Details

Date Published: 1 March 1991
PDF: 12 pages
Proc. SPIE 1468, Applications of Artificial Intelligence IX, (1 March 1991); doi: 10.1117/12.45520
Show Author Affiliations
Glenn Healey, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 1468:
Applications of Artificial Intelligence IX
Mohan M. Trivedi, Editor(s)

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