Computational geometry: an introduction
Computational geometry: an introduction
Detection of generalized principal axes is rotationally symmetric shapes
Pattern Recognition
Fast and Robust Smallest Enclosing Balls
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
Rectilinearity Measurements for Polygons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Notes on shape orientation where the standard method does not work
Pattern Recognition
Computer Vision and Image Understanding
Boundary based orientation of polygonal shapes
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
On the Orientability of Shapes
IEEE Transactions on Image Processing
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An orientability measure determines how orientable a shape is; i.e. how reliable an estimate of its orientation is likely to be. This is valuable since many methods for computing orientation fail for certain shapes. In this paper several existing orientability measures are discussed and several new orientability measures are introduced. The measures are compared and tested on synthetic and real data.