A novel method based on shape morphing is proposed for 2D shape recognition. In this framework, the shape of objects is described by using their contour. Shape recognition involves a morph between the contours of the objects being compared. The morph is quanti"ed by using a physics-based formulation. This quanti"cation is used as a dissimilarity measure to "nd the reference shape most similar to the input. The dissimilarity measure is shown to have the properties of a metric as well as invariance to Euclidean transformations. The recognition paradigm is applicable to both convex and non-convex shapes. Moreover, the applicability of the method is not constrained to closed shapes. Based on the metric properties of the dissimilarity method, a search strategy is described that obviates an exhaustive search of the template database during recognition experiments. Experimental results on the recognition of various types of shapes are presented.
Another method for 2D shape recognition is REF .
Planar shape recognition by shape morphing
Pattern Recognition
Computer Science Mathematics