Feature extraction in shape recognition using segmentation of the boundary curve

We present a new method for feature extraction of two-dimensional shape information based on segmentation of the boundary curve. This approach partitions closed shapes into segments and finds their angular spans. The number of segments and the angular spans form the first two feature parameters of a given shape. Fourier coefficients of all segments constitute the final feature parameters. The algorithm renders the shapes independent of scale, rotation and translation. The main advantage of this method is to speed up substantially the recognition process of the shapes, mainly because it is possible to design the classification rule in a hierarchical way. It is therefore suitable for objects to be sorted in a factory environment where the silhouette boundary supplies sufficient information for identification.