Study of phase congruency quantization function properties for image edge detection

Manuel G. Forero; Carlos A. Jacanamejoy; Santiago Rivera-Nieto

doi:10.1117/12.2594759

1 August 2021 Study of phase congruency quantization function properties for image edge detection

Manuel G. Forero, Carlos A. Jacanamejoy, Santiago Rivera-Nieto

Proceedings Volume 11842, Applications of Digital Image Processing XLIV; 118421G (2021) https://doi.org/10.1117/12.2594759
Event: SPIE Optical Engineering + Applications, 2021, San Diego, California, United States

Abstract

Phase congruency is a recently developed, but still rather unexplored and unknown technique for edge detection, allowing to determine the location of edges, ridges and valleys in images by analyzing the phase of the signal's frequency components. Phase congruency identifies edges based on the phase of the signal's frequency components. One of its main uses is image segmentation where the region of interest is separated from the background. The segmentation result varies according to a mathematical function, used to quantify the phase congruency, whose main properties are that it is centered at the origin, of even symmetry and whose global maximum is one. In addition, according to its form, a function allows better edge detection. Thus, several mathematical functions fulfill the necessary conditions for measuring phase congruency. However, these conditions have not yet been studied and, therefore, the type of changes they produce in phase congruency when varying this function is unknown. Therefore, in this work, an evaluation of the characteristics of the functions used for the quantification of phase congruency is presented, observing their properties and the behavior of phase congruency, allowing to find the most appropriate functions depending on the type of edges to be detected.

Conference Presentation

Citation Download Citation

Manuel G. Forero, Carlos A. Jacanamejoy, and Santiago Rivera-Nieto "Study of phase congruency quantization function properties for image edge detection", Proc. SPIE 11842, Applications of Digital Image Processing XLIV, 118421G (1 August 2021); https://doi.org/10.1117/12.2594759

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