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Proceedings Paper

Neural-network-based object recognition scheme directly from the boundary information
Author(s): Kootala P. Venugopal; Anil D. Mandalia; S. Abusalah
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Paper Abstract

We describe a neural network based recognition scheme for 2-D objects directly from the boundary information. The encoded boundary of the object is directly fed as input to the neural network cutting short the feature extraction stage and hence making the scheme computationally simpler. Also, the described scheme is invariant to translation, rotation, and scale changes to the objects. Using isolated hand-written digits, we show that the proposed scheme provides recognition accuracy of up to 87%. The error backpropagation method is used as the learning algorithm for the neural network.

Paper Details

Date Published: 9 July 1992
PDF: 8 pages
Proc. SPIE 1699, Signal Processing, Sensor Fusion, and Target Recognition, (9 July 1992); doi: 10.1117/12.138219
Show Author Affiliations
Kootala P. Venugopal, Florida Atlantic Univ. (United States)
Anil D. Mandalia, Florida Atlantic Univ. (United States)
S. Abusalah, Florida Atlantic Univ. (United States)

Published in SPIE Proceedings Vol. 1699:
Signal Processing, Sensor Fusion, and Target Recognition
Vibeke Libby; Ivan Kadar, Editor(s)

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