Discrete circles measurement for industrial inspection

Fabrice Mairesse; Tadeusz Sliwa; Stéphane Binczak; Yvon Voisin

doi:10.1117/12.642326

9 February 2006 Discrete circles measurement for industrial inspection

Fabrice Mairesse, Tadeusz Sliwa, Stéphane Binczak, Yvon Voisin

Proceedings Volume 6070, Machine Vision Applications in Industrial Inspection XIV; 60700K (2006) https://doi.org/10.1117/12.642326
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

Abstract

This article deals with the problem of the determination of characteristics of imperfect circular objects on discrete images mainly the radius and center's coordinates. Imperfections are provided by discretization, noise and interior distortions present in some production processes. To this end, a multi-level method based on active contours was developed and tested on, noisy or not, misshaped or not, simulated circles whom centers and radius were known. The adequacy of this approach was tested with several methods, among them several Radon based ones. More particularly, this study indicates the relevance of the use of active contours combined with a Radon transform based method, using a description of circles from their tangents, improved thanks to a fitting considering the discrete implementation of Radon transform. Through this study, an active region algorithm based on stationary states of a non linear diffusion principle is proposed. Its originality is to obtain a set of geometric envelopes in one pass, with a correspondence between level threshold of the grayscale result and a regularity scale, more or less close to the original shape. This set of geometric envelopes gives a multiscale representation, from a very regular approximation to a full detailed and roughest representation. Then, a more robust measure of the circle parameters can be computed.

Citation Download Citation

Fabrice Mairesse, Tadeusz Sliwa, Stéphane Binczak, and Yvon Voisin "Discrete circles measurement for industrial inspection", Proc. SPIE 6070, Machine Vision Applications in Industrial Inspection XIV, 60700K (9 February 2006); https://doi.org/10.1117/12.642326

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