This paper introduces a family of rectangularity measures. Several rectangularity measures already exist in literature, and all of them evaluate how much the shape considered differs from a perfect rectangle. But all existing measures assume that all rectangles have the same shape, and a consequence is that these measures do not distinguish among the rectangles whose edge-ration differs. In this paper we consider that differently elongated rectangles have different shape and propose a family of new rectangularity measures which distinguish among such rectangles. New rectangularity measures are invariant with respect to translation, rotation and scaling transformations. In addition, we introduce a tuning parameter which enables an additional flexibility of the new measures with respect to performing applications.

Measuring shape rectangularities

Dragisa Zunic;
2011-01-01

Abstract

This paper introduces a family of rectangularity measures. Several rectangularity measures already exist in literature, and all of them evaluate how much the shape considered differs from a perfect rectangle. But all existing measures assume that all rectangles have the same shape, and a consequence is that these measures do not distinguish among the rectangles whose edge-ration differs. In this paper we consider that differently elongated rectangles have different shape and propose a family of new rectangularity measures which distinguish among such rectangles. New rectangularity measures are invariant with respect to translation, rotation and scaling transformations. In addition, we introduce a tuning parameter which enables an additional flexibility of the new measures with respect to performing applications.
2011
9781467307529
Shape, rectangularity, measuring shape, image retrieval, image processing, computer vision
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12571/37146
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