1 February 1991 Issues in parallelism in object recognition
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Proceedings Volume 1384, High-Speed Inspection Architectures, Barcoding, and Character Recognition; (1991); doi: 10.1117/12.25338
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Abstract
Serial implementation of conventional object recognition techniques such as Hough Clustering and Interpretation Tree search perform poorly when faced with the combinatorial explosion of the search space especially in multiple-object scenes with partial occlusion. Parallelization of object recognition techniques therefore is an attractive proposition. The two issues that concern data parallelism are choice of multiprocessing granularity and choice of multiprocessing control. This paper shows a direct correspondence between the the choice of multiprocessing granularity and the granularity of representation of the image features and the object model features and also the direct correspondence between the choice of multiprocessing control and choice of constraint propagation technique. This paper cites two examples of parallelization of object recognition techniques - one based on Jjough Clustering and the other on Interpretation Tree search. Both examples are examined in the light of the two issues that pertain to data parallelism.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Suchendra M. Bhandarkar, Minsoo Suk, "Issues in parallelism in object recognition", Proc. SPIE 1384, High-Speed Inspection Architectures, Barcoding, and Character Recognition, (1 February 1991); doi: 10.1117/12.25338; https://doi.org/10.1117/12.25338
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KEYWORDS
Sensors

Object recognition

Image processing

Inspection

Optical character recognition

Curium

Spherical lenses

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