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Optoelectronic 3-D Object Classification From 2-D Images

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2 Author(s)
Chye-Hwa Loo ; Dept. of Ele.ctr. Eng., Univ. of Mississippi, Oxford, MS ; Elsherbeni, A.Z.

The task of object classification is complicated by variations in the 3-D object, which translate into distortions in 2-D images. The pattern matching for 3-D invariance classification requires a large amount of data and computation time. Proposed here is an efficient 3-D object classification algorithm for real-time fringe-adjusted joint transform correlator (FJTC)-based automatic target recognition (ATR) system. The proposed classification technique employed a fragment-based recognition approach and a new type of synthetic discriminant function filter in the generation of distortion-invariant correlation filter sets. The optoelectronic FJTC is then used to provide correlation of the filter sets with the input under a proper arrangement. This classification method is simple and fast, hence is suitable to be in use by real-time ATR systems. For the conclusion, simulation results are provided to prove the effectiveness of the proposed system in the classification of objects invariant to 3-D out-of-plane rotation distortion.

Published in:

Lightwave Technology, Journal of  (Volume:26 ,  Issue: 18 )

Date of Publication:

Sept.15, 2008

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