Corner detection in color images through a multiscale combination of end-stopped cortical cells

We assess the corner-detection capabilities of a model for endstopped cells in the visual cortex (Heitger et al., 1992). The responses of one of these cells alone can not account for the percept of a corner. This shortcoming can be greatly alleviated by a combination over several scales. The resulting corner detection method can deal with high frequency texture, low contrast, and rounded corners and is competitive in comparison with other corner detectors. Starting from known cortical cell types we hypothesize a color-sensitive equivalent of simple cells. This allows to extend corner detection to color-sensitive channels. The combination of grey-scale and color corner-detection yields a biologically plausible model of corner perception and may also be of interest for computer vision applications.