Pattern regularity as a visual key

This paper gives a summary of our research on pattern regularity. Periodic structures are perceived by humans as regular in a wide range of viewing angles. This observation motivates the development of a regularity based feature vector whose affine invariance is justified theoretically and tested experimentally. The vector is derived from the interaction map of a pattern. Several alternative but closely related definitions of the interaction map are discussed. The maximal regularity, a component of the feature vector, is shown to be consistent with human judgement on regularity. This feature can be implemented as a run filter, allowing for regularity based image filtering. Three applications of the regularity approach are presented. First, it is used for affine-invariant texture classification. Then, detection of periodic structures in aerial images is demonstrated. Finally, the texture inspection problem is addressed and structural defects are found as locations of low regularity. (C) 2000 Elsevier Science B.V. All rights reserved.