Abstract
In this paper, we study three basic novel measures of convexity for shape analysis. The convexity considered here is the so-called Q-convexity, that is, convexity by quadrants. The measures are based on the geometrical properties of Q-convex shapes and have the following features: (1) their values range from 0 to 1; (2) their values equal 1 if and only if the binary image is Q-convex; and (3) they are invariant by translation, reflection, and rotation by 90 degrees. We design a new algorithm for the computation of the measures whose time complexity is linear in the size of the binary image representation. We investigate the properties of our measures by solving object ranking problems and give an illustrative example of how these convexity descriptors can be utilized in classification problems.
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