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R Corresponding author. Pattern Recognition 32 (1999) 339--355

Summary: R Corresponding author.
Pattern Recognition 32 (1999) 339--355
3D object identification with color and curvature signatures
Adnan A.Y. Mustafa *, Linda G. Shapiro , Mark A. Ganter
Department of Mechanical and Industrial Engineering, Kuwait University, PO Box 5969, Safat-13060, Kuwait
Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, U.S.A.
Department of Mechanical Engineering University of Washington Seattle, WA 98195, U.S.A.
Received 11 February 1997; received in revised form 10 February 1998
In this paper we describe a model-based object identification system. Given a set of 3D objects and a scene containing
one or more of these objects, the system identifies which objects appear in the scene by matching surface signatures.
Surface signatures are feature vectors that reflect the probability of occurrence of the features for a given surface. Two
types of surface signatures are employed; curvature signatures and spectral (i.e. color) signatures. Furthermore, the
system employs an inexpensive acquisition setup consisting of a single CCD camera and two light sources. The system
has been tested on 95 observed surfaces and 77 objects with varying degrees of curvature and color with good results.
1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Keywords: Object identification; Object recognition; Color photometric stereo; Surface signatures; Surface matching; Color
1. Introduction
At the core of any complete vision system is the recog-
nition subsystem that generates hypotheses about objects


Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle


Collections: Computer Technologies and Information Sciences