Shift- and rotation-invariant interpattern heteroassociation model

Francis T. S. Yu; Chii-Maw Uang; Shizhuo Yin

doi:10.1117/12.160318

25 October 1993 Shift- and rotation-invariant interpattern heteroassociation model

Francis T. S. Yu, Chii-Maw Uang, Shizhuo Yin

Proceedings Volume 1959, Optical Pattern Recognition IV; (1993) https://doi.org/10.1117/12.160318
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

A shift and rotation invariant neural network using interpattern hetero association (IHA) model is illustrated. To preserve the shift and rotation invariant properties, a set of binarized-encoded circular harmonic expansion (CHE) function at the Fourier domain is used as the training set. The interconnection weight matrix is constructed using an IHA model. By using the shift and symmetric properties of the modulus Fourier spectral, the problem of centering the CHE functions can be avoided. Computer simulations and experimental demonstrations are provided in which we have shown that the shift and rotation invariant properties of the proposed IHA neural net are indeed preserved.

Citation Download Citation

Francis T. S. Yu, Chii-Maw Uang, and Shizhuo Yin "Shift- and rotation-invariant interpattern heteroassociation model", Proc. SPIE 1959, Optical Pattern Recognition IV, (25 October 1993); https://doi.org/10.1117/12.160318

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