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10 October 1994 Combining edge and surface information for object recognition
Neelima Shrikhande, Gongzhu Hu
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Proceedings Volume 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision; (1994) https://doi.org/10.1117/12.188932
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States
Abstract
One of the central problems of computer vision is model based object recognition. A catalogue of model objects is described via a set of features which are matched with the images. Image features that are most important to object recognition can be categorized into two types: edges and regions. Edges and surface patches are obtained from intensity and range images via independent algorithms. In this paper, we describe an algorithm that sets up a correspondence between the edge and surface features in a multiobject scene. Each edge is labeled with a list of surfaces to which it belongs and each surface is labeled with a list of edges that are on its boundary. This information can then be passed to higher level routines to group into individual objects for scene analysis. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested. Results appear quite encouraging.
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Neelima Shrikhande and Gongzhu Hu "Combining edge and surface information for object recognition", Proc. SPIE 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision, (10 October 1994); https://doi.org/10.1117/12.188932
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KEYWORDS
Object recognition
Detection and tracking algorithms
Edge detection
Image segmentation
Algorithm development
Image processing algorithms and systems
Visual process modeling
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