Optimised cubic spline approximations of image contours using points suppression

In this study, the author presents an algorithm for approximating the contour of a digital planar image by cubic splines. In the authors’ method, a subset of points (called corners) from the contour is selected. These corners are used to segment the contour and each segment is then approximated by a cubic spline. Parameters of the fitted splines are estimated by optimisation methods. The novelty of the proposed approach lies in the way the corners are selected. An initial set of corners are first selected using a process which is called as iterative points-suppression. This initial set is further reduced by a novel technique termed spline-suppression. The result is a very compact cubic spline representation of the contour using few corners on the contour. The effectiveness of the proposed method is demonstrated on two large databases: MPEG7_CE-Shape-1_Part_B database and a database of handwritten characters.

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