Uncertainty principles, extractors, and explicit embeddings of l2 into l1
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Detecting the most unusual part of a digital image
IWCIA'08 Proceedings of the 12th international conference on Combinatorial image analysis
Detection of Unusual Objects and Temporal Patterns in EEG Video Recordings
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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The purpose of this paper is to introduce an algorithm that can detect the most unusual part of a digital image in probabilistic setting. The most unusual part of a given shape is defined as a part of the image that has the maximal distance to all non-intersecting shapes with the same form. The method is tested on two- and three-dimensional images and has shown very good results without any predefined model. A version of the method independent of the contrast of the image is considered and is found to be useful for finding the most unusual part (and the most similar part) of the image conditioned on given image. The results can be used to scan large image databases, as for example medical databases.