Autonomous neuromorphic image understanding system using graph representation: lower-level design

Nikolaos G. Bourbakis; J. Sukaro Mertoguno

doi:10.1117/12.146688

10 June 1993 Autonomous neuromorphic image understanding system using graph representation: lower-level design

Nikolaos G. Bourbakis, J. Sukaro Mertoguno

Proceedings Volume 1904, Image Modeling; (1993) https://doi.org/10.1117/12.146688
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

Abstract

In this paper, a neuromorphic multilayer architecture, called KYDON, is presented. In particular, the structural design of the layer nodes and the low and high level vision tasks performed by KYDON nets are described. KYDON architecture has 'k' layers of nodes connected in full hexagonal mesh connectivity. The lowest layer capture images from the environment by employing 2-D photoarray. The top most layer deals with image interpretation and understanding. The intermediate layers perform various process to bridge the bottom most layer to the top most layer. KYDON use graph to represent the knowledge, extracted from the image. An important feature of KYDON is that KYDON does not have any host computer or control processor to handle I/O and other miscellaneous tasks.

Citation Download Citation

Nikolaos G. Bourbakis and J. Sukaro Mertoguno "Autonomous neuromorphic image understanding system using graph representation: lower-level design", Proc. SPIE 1904, Image Modeling, (10 June 1993); https://doi.org/10.1117/12.146688

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