robust ring (and circle) detection algorithm
Dear Devs, In the process of tracking objects under the microscope I was confronted with an image analysis problem, for which I could not find a satisfactory solution in איק standard scientific packages (nor in the literature survey I made). At the time I started this, scikit-image did not include a circle Hough transform and OpenCV's was not good enough. I ended up developing an algorithm myself, which can be regarded as an off-spring of the circle Hough transform. I summarised the work in a manuscript titled: "*Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging*" (a pre-print is available at arXiv:1310.1371 <http://arxiv.org/abs/1310.1371>). NB, it was written minded at potential users and applications rather than computer scientists, which I am not. I would like to make the code publicly available. I believe it may be beneficial to the scikit-image community and users as a practical alternative to the current Standard Circle Hough transform. I contacted Stéfan van der Walt, who expressed interest in the algorithm. I would be grateful to have your feedback, any input would be helpful! With kind thanks to all contributors, Eldad -- Eldad Afik Physics of Complex Systems Weizmann Institute of Science *Some technical notes:* A* typical example *of the images I need to analyse can be found in the manuscript arXiv:1310.1371 <http://arxiv.org/abs/1310.1371> (Fig. 1a as well as S2a). The *results* of the software I wrote exhibit a detection rate which exceeds 94% and have only 1% false-detection, providing sub-pixel accuracy. The conceptual steps in making the algorithm* robust* are sketched in Fig. 2. The main steps to make it* efficient*, both in execution-time as well as memory consumption, are outlines on page 8; more technical details in this respect can be found in the "Supporting Information" Text section. The "methods" section of the manuscript provides some details regarding the *benchmarking*.
Hi Eldad, I'm interested in this but don't have the bandwidth to review this until next week at the earliest. If no one steps up before then I'll keep you posted! Juan. — Sent from Mailbox for iPhone On Sun, Mar 9, 2014 at 11:05 PM, Eldad Afik <eldad.afik@gmail.com> wrote:
Dear Devs, In the process of tracking objects under the microscope I was confronted with an image analysis problem, for which I could not find a satisfactory solution in איק standard scientific packages (nor in the literature survey I made). At the time I started this, scikit-image did not include a circle Hough transform and OpenCV's was not good enough. I ended up developing an algorithm myself, which can be regarded as an off-spring of the circle Hough transform. I summarised the work in a manuscript titled: "*Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging*" (a pre-print is available at arXiv:1310.1371 <http://arxiv.org/abs/1310.1371>). NB, it was written minded at potential users and applications rather than computer scientists, which I am not. I would like to make the code publicly available. I believe it may be beneficial to the scikit-image community and users as a practical alternative to the current Standard Circle Hough transform. I contacted Stéfan van der Walt, who expressed interest in the algorithm. I would be grateful to have your feedback, any input would be helpful! With kind thanks to all contributors, Eldad -- Eldad Afik Physics of Complex Systems Weizmann Institute of Science *Some technical notes:* A* typical example *of the images I need to analyse can be found in the manuscript arXiv:1310.1371 <http://arxiv.org/abs/1310.1371> (Fig. 1a as well as S2a). The *results* of the software I wrote exhibit a detection rate which exceeds 94% and have only 1% false-detection, providing sub-pixel accuracy. The conceptual steps in making the algorithm* robust* are sketched in Fig. 2. The main steps to make it* efficient*, both in execution-time as well as memory consumption, are outlines on page 8; more technical details in this respect can be found in the "Supporting Information" Text section. The "methods" section of the manuscript provides some details regarding the *benchmarking*. -- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
Hi Eldad On Sun, Mar 9, 2014 at 3:28 PM, Eldad Afik <eldad.afik@gmail.com> wrote:
I summarised the work in a manuscript titled: "Robust and highly performant ring detection algorithm for 3d particle tracking using 2d microscope imaging" (a pre-print is available at arXiv:1310.1371). NB, it was written minded at potential users and applications rather than computer scientists, which I am not.
Shall we start working on a pull request with a proof of concept illustration? Stéfan
participants (3)
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Eldad Afik -
Juan Nunez-Iglesias -
Stéfan van der Walt