Loughborough University
Chong-IEEE Access- 2015-accepted.pdf (1.59 MB)
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Wrinkle detection using hessian line tracking

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journal contribution
posted on 2016-02-09, 12:59 authored by Choon-Ching Ng, Moi Hoon Yap, Nicholas Costen, Baihua LiBaihua Li
Wrinkles play an important role in face-based analysis. They have been widely used in applications such as facial retouching, facial expression recognition and face age estimation. Although a few techniques for wrinkle analysis have been explored in the literature, poor detection limits the accuracy and reliability of wrinkle segmentation. Therefore, an automated wrinkle detection method is crucial to maintain consistency and reduce human error. In this paper, we propose Hessian line tracking (HLT) to overcome the identified problem. The proposed HLT is composed of Hessian seeding and directional line tracking. It is an extension of a Hessian filter; however it significantly increases the accuracy of wrinkle localization when compared with existing methods. In the experimental phase, three coders were instructed to annotate wrinkles manually. To assess the manual annotation, both intra- and inter-reliability were measured, with an accuracy of 94% or above. Experimental results show that the proposed method is capable of tracking hidden pixels; thus it increases connectivity of detection in between wrinkles, allowing some fine wrinkles to be detected. In comparison to the stateof- the-art methods such as the Cula method, Frangi filter, and hybrid Hessian filter, the proposed HLT yields better results, with an accuracy of 84%. This work demonstrates that HLT is a remarkably strong detector of forehead wrinkles in 2D images.



  • Science


  • Computer Science

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IEEE Access




1079 - 1088


NG, C.-C. ... et al, 2015. Wrinkle detection using hessian line tracking. IEEE Access, 3, pp.1079-1088




  • AM (Accepted Manuscript)

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This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

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This is the accepted manuscript version of the paper. © 2015 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.




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