Title: Improving ear recognition robustness against 3D rotation using statistical modelling based on forensic classification

Authors: T. Minamidani; H. Sai; D. Watabe

Addresses: Saitama Institute of Technology, Fukaya, 369-0293, Japan ' Saitama Institute of Technology, Fukaya, 369-0293, Japan ' Saitama Institute of Technology, Fukaya, 369-0293, Japan

Abstract: Even though ear shape is used in forensic investigations, an ear identification system for assisting forensic experts is not well developed. One of the reasons for this is the three-dimensional (3D) concave shape of the ear; this changes its two-dimensional (2D) appearance when camera angles change. 3D statistical modelling is necessary to compensate for these changes in 2D appearance. In this study, we aim to increase the number of 3D statistical ear models based on a few forensic classification methods of ear shapes. Experimental evaluation shows that morphological classification based on the antihelix can improve the robustness of ear recognition against the change in camera angles.

Keywords: ear recognition robustness; three-dimensional rotation; statistical modelling; forensic classification; ear shapes; ear identification systems; camera angle change; three-dimensional statistical ear models; morphological classification; antihelix; ear feature points; Gabor features; AKAZE features.

DOI: 10.1504/IJBM.2019.102876

International Journal of Biometrics, 2019 Vol.11 No.4, pp.372 - 388

Received: 06 Apr 2018
Accepted: 16 Apr 2019
Published online: 08 Oct 2019 *

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