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

Willcocks, Chris and Jackson, Philip T.G. and Nelson, Carl J. and Obara, Boguslaw (2016) 'Extracting 3D parametric curves from 2D images of helical objects.', IEEE transactions on pattern analysis and machine intelligence., 39 (9). pp. 1757-1769.

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.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1109/TPAMI.2016.2613866
Publisher statement:© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:20 September 2016
Date deposited:23 September 2016
Date of first online publication:26 September 2016
Date first made open access:23 September 2016

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