Extracting 3D parametric curves from 2D images of helical objects

Willcocks, Chris; Jackson, Philip T.G.; Nelson, Carl J.; Obara, Boguslaw

Abstract

Helical objects occur in medicine, biology, cosmetics, nanotechnology, and engineering. Extracting a 3D parametric curve from a 2D image of a helical object has many practical applications, in particular being able to extract metrics such as tortuosity, frequency, and pitch. We present a method that is able to straighten the image object and derive a robust 3D helical curve from peaks in the object boundary. The algorithm has a small number of stable parameters that require little tuning, and the curve is validated against both synthetic and real-world data. The results show that the extracted 3D curve comes within close Hausdorff distance to the ground truth, and has near identical tortuosity for helical objects with a circular profile. Parameter insensitivity and robustness against high levels of image noise are demonstrated thoroughly and quantitatively.

Citation

Willcocks, C., Jackson, P. T., Nelson, C. J., & Obara, B. (2016). Extracting 3D parametric curves from 2D images of helical objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(9), 1757-1769. https://doi.org/10.1109/tpami.2016.2613866

• Journal Article Type: Article
• Acceptance Date: Sep 20, 2016
• Online Publication Date: Sep 26, 2016
• Publication Date: Sep 26, 2016
• Deposit Date: Sep 23, 2016
• Publicly Available Date: Sep 23, 2016
• Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
• Print ISSN: 0162-8828
• Electronic ISSN: 1939-3539
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 9
• Pages: 1757-1769
• DOI: https://doi.org/10.1109/tpami.2016.2613866
• Public URL: https://durham-repository.worktribe.com/output/1376088