Search-by-content of partially occluded images

Abstract.

This paper describes a method for searching images by content that compensates for occlusions in the image. The method extends a search technique proposed by Stone and Li that is based on two criteria – sum of squares differences and average intensity, but the method can be used in conjunction with other criteria, including the normalized correlation coefficient. Image occlusions have a profound impact on template-matching image searches. A typical example of such an occlusion is a cloud over a land mass in an image taken from a satellite. Searches performed without compensation for occlusions are unable to detect matches in positions near the cloud perimeter that are not totally obscured by the cloud. The compensation method introduced here can discover good matches in regions where patterns overlap occluded regions, and would otherwise be missed. The key idea of the algorithm is to perform computations in a way that removes invalid pixels from summations. The enhanced algorithm requires no more than a factor of two increase in storage and computation costs as compared to the Stone–Li algorithm.