Effective classification of planar shapes based on curve segment properties

In this paper, a pattern classifier for recognition of planar contours is developed based on the curve bend function (CBF). The CBF makes use of both the curve bend angle which measures the bend degree of a curve segment of a contour and the type coefficient which indicates whether the curve segment is convex or concave, i.e., the related corner on the contour is an inner or outer angle. The information of a contour obtained by its CBF is sufficient to represent its main features. The classifier is designed by using the properties of the CBF directly, and its training process is simpler than other kinds of classifiers, such as neural networks. Our experimental results demonstrate that the classifier is robust for planar shape classification. © 1997 Published by Elsevier Science B.V.