Improving ear recognition robustness against 3D rotation using statistical modelling based on forensic classification. (5th September 2019)

• Record Type: Journal Article
• Authors: Minamidani, T.; Sai, H.; Watabe, D.
• Is Part Of: International journal of biometrics. Volume 11:Number 4(2019)
• Page Start: 372
• Page End: 388
• Publication Date: 2019-09-05
• Subjects: 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; Biometric identification -- Periodicals; Biometry -- Periodicals; 570.15195
• Languages: English
• ISSNs: 1755-8301

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.