Improved grating and bar cell models in cortical area V1 and texture coding

This paper presents improved models of cortical neurons in V1 that act like grating and bar detectors. Both models use the same frontend, which consists of a contrast normalisation in combination with isotropic DOG filtering, followed by anisotropic Gabor filtering together with a response sharpening. Different grouping processes of ON and OFF responses lead to a very selective detection of bar width and grating frequency, with a good localisation. Furthermore, outputs of grating cells can be grouped over combinations of orientations for coding nonlinear textures. It is shown that these models, apart from being used in the modelling of the visual cortex, can be employed in pattern-recognition applications.