Effect of Barrel Distortion and Super-Resolution for Single-View-Based Ear Biometrics Rotated in Depth

Watabe, Daishi; Minamidani, Takanari; Zhao, Wenbo; Sai, Hideyasu; Cao, Jianting

doi:10.1109/icbake.2013.49

Cited by 7 publications

(3 citation statements)

References 9 publications

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“…Moreover, super‐resolution techniques might be of particular interest in case video footage is available. These methods could be employed in order to reduce compression artefacts and hence improve the robustness and biometric performance of an ear recognition system [41]. Further, feature fusion approaches [9, 11, 72] could be utilised to bridge the observed performance gap between systems operating on raw and highly compressed images.…”

Section: Discussionmentioning

confidence: 99%

“…It was found that while conventional detection algorithms appear rather robust in presence of these signal degradations, recognition algorithms are highly influenced by noise causing a significant decrease in accuracy for images exhibiting peak signal to noise ratio (PSNR) values of 20-30 dB. Further, effects of barrel distortion and super-resolution on ear biometrics are investigated in [41]. It has been empirically shown that biometric performance drops in case of barrel distorted images, which might be compensated by the use of super-resolution images for model normal vector creation.…”

Section: Iet Biometricsmentioning

confidence: 99%

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Effects of image compression on ear biometrics

et al. 2016

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An ear recognition system represents a powerful tool in forensic applications. Even in case the facial characteristic of a suspect is partly or fully covered an image of the outer ear may suffice to reveal a subject's identity. In forensic scenarios imagery may stem from surveillance cameras of environments where image compression is common practice to overcome limitations of storage or transmission capacities. Yet, the impact of severe image compression on ear recognition has remained undocumented. In this work the authors analyse the influence of different state-of-the-art image compression standards on ear detection and ear recognition algorithms. Evaluations conducted on an uncompressed ear database are considered with respect to different stages in the processing chain of an ear recognition system where compression may be applied, representing the most relevant forensic scenarios. Experimental results are discussed in detail highlighting the potential and limitations of automated ear recognition in presence of image compression.

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Section: Discussionmentioning

confidence: 99%

Section: Iet Biometricsmentioning

confidence: 99%

Effects of image compression on ear biometrics

et al. 2016

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“…In research on biometric authentication technology, authentication methods using moving images of the pinna, the external part of the ear in humans and other mammals, have been studied [1]. Several studies have concluded that the shape of the pinna is complex and differs significantly across individuals [2][3][4][5]. Conventional studies indicate the feasibility of an authentication system using the acoustic transfer functions of the pinna and the ear canal [6].…”

Section: Introductionmentioning

confidence: 99%

Multimodal Personal Ear Authentication Using Smartphones

Itani¹,

Kita²,

Kajikawa³

2021

Preprint

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In recent years, biometric authentication technology for smartphones has become widespread, with the mainstream methods being fingerprint authentication and face recognition. However, fingerprint authentication cannot be used when hands are wet, and face recognition cannot be used when a person is wearing a mask. Therefore, we examine a personal authentication system using the pinna as a new approach for biometric authentication on smartphones. Authentication systems based on the acoustic transfer function of the pinna (PRTF: Pinna Related Transfer Function) have been investigated. However, the authentication accuracy decreases due to the positional fluctuation across each measurement. In this paper, we propose multimodal personal authentication on smartphones using PRTF. The pinna image and positional sensor information are used with the PRTF, and the effectiveness of the authentication method is examined. We demonstrate that the proposed authentication system can compensate for the positional changes in each measurement and improve the robustness.

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