Computer-Aided Design
Detection of generalized principal axes is rotationally symmetric shapes
Pattern Recognition
Computing deviations from convexity in polygons
Pattern Recognition Letters
Machine vision
Techniques for Assessing Polygonal Approximations of Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the minimum-area encasing rectangle for an arbitrary closed curve
Communications of the ACM
Robot Vision
Statistical Shape Features for Content-Based Image Retrieval
Journal of Mathematical Imaging and Vision
Measuring shape: ellipticity, rectangularity, and triangularity
Machine Vision and Applications
A Comparative Evaluation of Length Estimators of Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Convexity Measure for Polygons
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Convexity Measure Based on a Probabilistic Interpretation of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
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
Boundary based orientation of polygonal shapes
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
A Hu moment invariant as a shape circularity measure
Pattern Recognition
Measuring Cubeness of 3D Shapes
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Shape elongation from optimal encasing rectangles
Computers & Mathematics with Applications
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Tunable cubeness measures for 3D shapes
Pattern Recognition Letters
Measuring linearity of open planar curve segments
Image and Vision Computing
ADR shape descriptor - Distance between shape centroids versus shape diameter
Computer Vision and Image Understanding
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Shape elongation is one of the basic shape descriptors that has a very clear intuitive meaning. That is the reason for its applicability in many shape classification tasks. In this paper we define a new method for computing shape elongation. The new measure is boundary based and uses all the boundary points. We start with shapes having polygonal boundaries. After that we extend the method to shapes with arbitrary boundaries. The new elongation measure converges when the assigned polygonal approximation converges toward a shape. We express the measure with closed formulas in both cases: for polygonal shapes and for arbitrary shapes. The new measure finds the elongation for shapes whose boundary is not extracted completely, which is impossible to achieve with area based measures.