Abstract
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.
© 2008 IEEE
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