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The University of Western Australia

Department of Computer Science

Technical Report 95/4

March 1995

Revised June 1995

Image Features From

Phase Congruency

Peter Kovesi

Robotics and Vision Research Group


Image features such as step edges, lines and Mach bands all give rise to points where the Fourier components of the image are maximally in phase. The use of phase congruency for marking features has significant advantages over gradient based methods. It is a dimensionless quantity that is invariant to changes in image brightness or contrast, hence it provides an absolute measure of the significance of feature points. This allows the use of universal threshold values that can be applied over wide classes of images. This paper presents a new way of calculating phase congruency through the use of wavelets. The existing theory that has been developed for 1D signals is extended to allow the calculation of phase congruency in 2D images. It is shown that for good localization it is important to consider the spread of frequencies present at a point of phase congruency. An effective method for identifying, and compensating for, the level of noise in an image is presented. Finally, it is argued that high-pass filtering should be used to obtain image information at different scales. With this approach the choice of scale only affects the relative significance of features without degrading their localization.

computer vision, feature detection, phase congruency

CR categories