Frequency Domain Characterization Of Synthetic Discriminant Functions

B. V.K. Vijaya Kumar; Zouhir Bahri

doi:10.1117/12.942720

19 February 1988 Frequency Domain Characterization Of Synthetic Discriminant Functions

B. V.K. Vijaya Kumar, Zouhir Bahri

Proceedings Volume 0848, Intelligent Robots and Computer Vision VI; (1988) https://doi.org/10.1117/12.942720
Event: Advances in Intelligent Robotics Systems, 1987, Cambridge, CA, United States

Abstract

Synthetic Discriminant Functions (SDF's) constitute an approach to distortion-invariant pattern recognition when sufficiently descriptive training images are available. Traditionally, the SDF's have been designed in the image space even though their eventual implementation in optical processors requires the fabrication of Computer Generated Holograms (CGH's) that can be placed in the frequency plane of optical correlators. With this consideration, we formulate the SDF problem in the frequency domain and characterize the set containing all the solutions. This conversion of the SDF problem from space domain to frequency domain requires that we define a "pseudo-DFT" operation. Relevant properties of this new operation are proved. This formal mathematical characterization of the frequency-domain SDF solutions allows us to select solutions with attractive features such as having unit magnitude (phase only) or only two amplitude levels (suitable for ON-OFF devices).

Citation Download Citation

B. V.K. Vijaya Kumar and Zouhir Bahri "Frequency Domain Characterization Of Synthetic Discriminant Functions", Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); https://doi.org/10.1117/12.942720

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