Optical-digital-neural network system for aided target recognition

Keith B. Farr; Richard L. Hartman

doi:10.1117/12.213078

5 July 1995 Optical-digital-neural network system for aided target recognition

Keith B. Farr, Richard L. Hartman

Author Affiliations +

Proceedings Volume 2485, Automatic Object Recognition V; (1995) https://doi.org/10.1117/12.213078
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Many military systems have a critical need for aided target recognition, or cuing. This includes several systems with wide field-of-view search missions such as the UAV, EFOG-M, and Comanche. This report discusses one new approach: a multiple region of interest processor based on diffraction pattern sampling and digital neural network processing. In this concept an optical system segments the image into multiple, rectangular regions of interest and in parallel converts each ROI, be it visible, IR, or radar, to a spatial frequency power spectrum and samples that spectrum for 64 features. A neural network learns to correlate those features with target classes or identifications. A digital system uses the network weights to recognize unknown targets. The research discussed in this report using a single ROI processor showed a very high level of performance. Out of 1024 trials with models of five targets of F- 14, F-18, HIND, SCUD, and M1 tanks, there were 1023 correct classifications and 1 incorrect classification. Out of 1514 trials with those images plus 490 real clutter scenes, there were 1514 correct decisions between target or no-target. Of the 1024 target detections, there were 1023 correct classifications. Out of 60 trials with low resolution IR images of real scenes, there were 60 correct decisions between target and no-target. Of the 40 target detections, there were 40 correct classifications.

Citation Download Citation

Keith B. Farr and Richard L. Hartman "Optical-digital-neural network system for aided target recognition", Proc. SPIE 2485, Automatic Object Recognition V, (5 July 1995); https://doi.org/10.1117/12.213078

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