3D ear shape reconstruction and recognition for biometric applications
This paper presents a new method based on a generalized neural reflectance (GNR) model for enhancing ear recognition under variations in illumination. It is based on training a number of synthesis images of each ear taken at single lighting direction with a single view. The way of synthesizing image...
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| Format: | Article |
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Springer Verlag
2013
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| Online Access: | https://eprints.nottingham.ac.uk/46758/ |
| _version_ | 1848797393649139712 |
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| author | Cho, Siu-Yeung |
| author_facet | Cho, Siu-Yeung |
| author_sort | Cho, Siu-Yeung |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper presents a new method based on a generalized neural reflectance (GNR) model for enhancing ear recognition under variations in illumination. It is based on training a number of synthesis images of each ear taken at single lighting direction with a single view. The way of synthesizing images can be used to build training cases for each ear under different known illumination conditions from which ear recognition can be significantly improved. Our training algorithm assigns to recognize the ear by similarity measure on ear features extracting firstly by the principal component analysis method and then further processing by the Fisher’s discriminant analysis to acquire lower-dimensional patterns. Experimental results conducted on our collected ear database show that lower error rates of individual and symmetry are achieved under different variations in lighting. The recognition performance of using our proposed GRN model significantly
outperforms the performance that without using the
proposed GNR model. |
| first_indexed | 2025-11-14T20:03:10Z |
| format | Article |
| id | nottingham-46758 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:03:10Z |
| publishDate | 2013 |
| publisher | Springer Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-467582018-06-06T10:23:12Z https://eprints.nottingham.ac.uk/46758/ 3D ear shape reconstruction and recognition for biometric applications Cho, Siu-Yeung This paper presents a new method based on a generalized neural reflectance (GNR) model for enhancing ear recognition under variations in illumination. It is based on training a number of synthesis images of each ear taken at single lighting direction with a single view. The way of synthesizing images can be used to build training cases for each ear under different known illumination conditions from which ear recognition can be significantly improved. Our training algorithm assigns to recognize the ear by similarity measure on ear features extracting firstly by the principal component analysis method and then further processing by the Fisher’s discriminant analysis to acquire lower-dimensional patterns. Experimental results conducted on our collected ear database show that lower error rates of individual and symmetry are achieved under different variations in lighting. The recognition performance of using our proposed GRN model significantly outperforms the performance that without using the proposed GNR model. Springer Verlag 2013-07 Article PeerReviewed Cho, Siu-Yeung (2013) 3D ear shape reconstruction and recognition for biometric applications. Signal, Image and Video Processing, 7 (4). pp. 609-618. ISSN 1863-1711 Ear recognition; 3D shape reconstruction; Principal component analysis; Fisher’s discriminant analysis https://link.springer.com/article/10.1007%2Fs11760-013-0481-y doi:10.1007/s11760-013-0481-y doi:10.1007/s11760-013-0481-y |
| spellingShingle | Ear recognition; 3D shape reconstruction; Principal component analysis; Fisher’s discriminant analysis Cho, Siu-Yeung 3D ear shape reconstruction and recognition for biometric applications |
| title | 3D ear shape reconstruction and recognition for biometric applications |
| title_full | 3D ear shape reconstruction and recognition for biometric applications |
| title_fullStr | 3D ear shape reconstruction and recognition for biometric applications |
| title_full_unstemmed | 3D ear shape reconstruction and recognition for biometric applications |
| title_short | 3D ear shape reconstruction and recognition for biometric applications |
| title_sort | 3d ear shape reconstruction and recognition for biometric applications |
| topic | Ear recognition; 3D shape reconstruction; Principal component analysis; Fisher’s discriminant analysis |
| url | https://eprints.nottingham.ac.uk/46758/ https://eprints.nottingham.ac.uk/46758/ https://eprints.nottingham.ac.uk/46758/ |