Lateral Inhibition in Cortical Filters

This work presents explorations in the microstructure of natural vision systems based on large scale computer simulations. Similarly to previous work in this area, we compute the functional inner products of a two-dimensional input signal (image) with a set of two-dimensional Gabor functions which have been shown to t the receptive elds of simple cells in the primary visual cortex of mammals. These inner products are then considered as net inputs to the cortical cells and used to compute the cell activations as non-linear functions. A previously used model is extended with a pixel-wise winner-takes-all competition between diierent Gabor lters which is introduced in order to model lateral inhibition between cortical cells. The eeect of lateral inhibition is qualitatively estimated by visualization of computed cortical images and quantitatively evaluated by applying the model to a face recognition problem. Recognition rate of 97% was achieved on a database of 205 face images of 30 persons vs. 94% achieved with a previously used model.