Selection of image primitives for general-purpose visual processing

The results of psychophysical experiments suggest the existence of a hierarchy of visual features based on the relations between image contours. The human visual system appears to be preattentively, selectively sensitive to image contours which contain certain of these features. These results can be used to develop computer vision algorithms for: (1) the selective enhancement of image contours which correlate with their perceptual significance; and (2) the segmentation of boundary images into sets which have a high probability of depicting a single object. The extreme simplicity of the algorithms, as well as their ability to generate perceptually significant results, demonstrate the advantages of using psychophysical results to uncover image invariants which correlate with the structure of the physical world that is of value for visual perception.