Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Nonlinear interaction of ON and OFF data streams for the detection of visual structure

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Littmann, E. ; Abt. Neuroinf., Ulm Univ., Germany ; Neumann, H. ; Pessoa, L.

Visual stimuli lead to neural activity in the retina that is propagated in separate ON and OFF pathways to the cortex. Most models of biological early vision recombine these activity streams by a linear integration at the simple cell level. Based on empirical as well as theoretical investigations we propose a nonlinear recombination circuit that is selectively responsive to contrast magnitude as well as to the sharpness of luminance transition. Simulations with artificial and camera images show a higher positional selectivity for local contrasts than an equivalent linear device. In a multiscale hierarchy the nonlinear circuit produces a unique maximum response in scale-space where scale directly relates to the width of the luminance transition. In order to investigate the biological relevance of the proposed neural circuit, we measured the model sensitivity to luminance gradient reversal in bar stimuli. Our simulations show strong similarity to simple cell recordings in the feline striate cortex. This result further supports the evidence for nonlinear interaction at the simple cell level

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996