Shape Discrimination Using Fourier Descriptors

TLDR

Fourier descriptors provide useful properties for discriminating boundary curves, an important problem in picture processing and pattern recognition. The authors review two types of Fourier descriptors, propose a distance measure based on them to quantify differences between boundary curves, and show how they can generate object skeletons. Experimental results demonstrate the method’s effectiveness in character recognition and machine parts recognition.

Abstract

Description or discrimination of boundary curves (shapes) is an important problem in picture processing and pattern recognition. Fourier descriptors (FD's) have interesting properties in this respect. First, a critical review is given of two kinds of FD's. Some properties of the FD's are given and a distance measure is proposed, in terms of FD's, that measures the difference between two boundary curves. It is shown how FD's can be used for obtaining skeletons of objects. Finally, experimental results are given in character recognition and machine parts recognition.