Distortion-invariant pattern recognition using composite Fourier plane nonlinear filtering

Bahram Javidi; Wenlu Wang; Guanshen Zhang

doi:10.1117/12.284203

24 October 1997 Distortion-invariant pattern recognition using composite Fourier plane nonlinear filtering

Bahram Javidi, Wenlu Wang, Guanshen Zhang

Proceedings Volume 3159, Algorithms, Devices, and Systems for Optical Information Processing; (1997) https://doi.org/10.1117/12.284203
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

In this paper we investigate composite Fourier-plane nonlinear filters for distortion invariant pattern recognition. Different types of noise such as spatially non-overlapping color background noise, other non-target object, real scene noise, and additive white noise are used to investigate the performance of the filter. Computer simulation results are presented to show the performance enhancement using Fourier-plane nonlinearities in the composite filter designs. The training image sets and the test image sets are generate by in-plane and out-plane rotation of different aircraft.

Citation Download Citation

Bahram Javidi, Wenlu Wang, and Guanshen Zhang "Distortion-invariant pattern recognition using composite Fourier plane nonlinear filtering", Proc. SPIE 3159, Algorithms, Devices, and Systems for Optical Information Processing, (24 October 1997); https://doi.org/10.1117/12.284203

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available