Circle Detection Performance Evaluation Revisited

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9657)


Circle and circular arc detection in images have been a long standing topic in image analysis. It finds numerous applications for both scanned document images as well as in photographic images. As a result, circle detection algorithms are published regularly and benchmarking data sets and contests have been organized on a regular basis over the last decades. Unfortunately, they have not been able to achieve a very clear image establishing which approaches perform best and under what exact conditions.

This paper contributes to circle and arc detection, by providing an open and fully reproducible framework for benchmarking and evaluating circle and circular arc detection methods. It builds upon the current state of the art and commonly used metrics by providing a complementary approach through the introduction of synthetic evaluation data for benchmarking versus two noise types at gradually varying noise levels and new performance metrics that are compatible with previous evaluation approaches.



The authors would like to thank Télécom Nancy students G. Humbert and Y. Jardin for their preliminary work, and all authors who were solicited and who kindly provided their source code, binary code or other contribution allowing us to fully evaluate their methods. E. Barney Smith was funded under the “Chercheur d’excellence” program by the Région Lorraine.


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Electrical and Computer Engineering DepartmentBoise State UniversityBoiseUSA
  2. 2.Université de Lorraine – Loria (UMR 7503)Vandœuvre-lès-Nancy CedexFrance

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