Finding corners in images by foveated search

We develop a new approach to finding corners in images that combines foveated edge detection and curvature calculation with saccadic placement of foveal fixations. Each saccade moves the fovea to a location of high curvature combined with high edge gradient. Edges are located using a foveated Canny edge detector with spatial constant that increases with eccentricity. Next, we calculate a measure of local corner strength, based on a product of curvature and gradient. An inhibition factor based on previous visits to a region of the image prevents the system from repeatedly returning to the same locale. A long saccade is move thes fovea to previously unexplored areas of the image. Subsequent short saccades improve the accuracy of the location of the corner approximated by the long saccade. The system is tested on two natural scenes and the results compared against subjects observing the same test images through an eyetracker. Results show that the algorithm is a good locator of corners.