Shape characterization of new apple cultivars by Fourier expansion of digitized images

Image processing is an important tool in quantifying the external appearance of fruits and vegetables. The shape, size, colour and absence of defects at the surface determine the appearance of a biological product. In this research, an image processing algorithm, based on Fourier expansion, was developed to characterize the shape of apples. This mathematical approach reduced the dimensionality of the edge points of an image to a set of 24 Fourier coefficients. Applying principal component analysis on the set of Fourier coefficients resulted in two shape variables to measure accurately the apple profiles, described by a subjective shape descriptor list. It was shown that four images per apple were needed to quantify the average shape of randomly chosen apple. The feasibility of the algorithms was demonstrated by distinguishing the shape of different experimental apple cultivars. (C) 1999 Silsoe Research Institute.