Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

Andrew Baek; Nabil H. Farhat

doi:10.1117/12.326749

14 October 1998 Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

Andrew Baek, Nabil H. Farhat

Proceedings Volume 3462, Radar Processing, Technology, and Applications III; (1998) https://doi.org/10.1117/12.326749
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.

Citation Download Citation

Andrew Baek and Nabil H. Farhat "Biomorphic networks: approach to invariant feature extraction and segmentation for ATR", Proc. SPIE 3462, Radar Processing, Technology, and Applications III, (14 October 1998); https://doi.org/10.1117/12.326749

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