EarVN1.0: A new large-scale ear images dataset in the wild

Ear recognition is starting to grow as an alternative to other biometric recognition types in recent years. The EarVN1.0 dataset is constructed by collecting ear images of 164 Asian peoples during 2018. It is among the largest ear datasets publicly to the research community which composed by 28,412...

Full description

Bibliographic Details
Main Author: Vinh Truong Hoang
Format: Article
Language:English
Published: Elsevier 2019-12-01
Series:Data in Brief
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340919309850
id doaj-acfdb75d9bfe4aaf9c1d9055f9fb2ba1
record_format Article
spelling doaj-acfdb75d9bfe4aaf9c1d9055f9fb2ba12020-11-25T01:38:53ZengElsevierData in Brief2352-34092019-12-0127EarVN1.0: A new large-scale ear images dataset in the wildVinh Truong Hoang0Faculty of Computer Science, Ho Chi Minh City Open University, Viet NamEar recognition is starting to grow as an alternative to other biometric recognition types in recent years. The EarVN1.0 dataset is constructed by collecting ear images of 164 Asian peoples during 2018. It is among the largest ear datasets publicly to the research community which composed by 28,412 colour images of 98 males and 66 females. Thus, this dataset is different from previous works by providing images of both ears per person under unconstrained conditions. The original facial images have been acquired by unconstrained environment including cameras systems and light condition. Ear images are then cropped from facial images over the large variations of pose, scale and illumination. Several machine learning tasks can be applied such as ear recognition, image classification or clustering, gender recognition, right-ear or left-ear detection and enhanced super resolution. Keywords: Ear recognition, Biometric, Image classification, Super-resolution, Image clustering, Right-ear or left-ear detectionhttp://www.sciencedirect.com/science/article/pii/S2352340919309850
collection DOAJ
language English
format Article
sources DOAJ
author Vinh Truong Hoang
spellingShingle Vinh Truong Hoang
EarVN1.0: A new large-scale ear images dataset in the wild
Data in Brief
author_facet Vinh Truong Hoang
author_sort Vinh Truong Hoang
title EarVN1.0: A new large-scale ear images dataset in the wild
title_short EarVN1.0: A new large-scale ear images dataset in the wild
title_full EarVN1.0: A new large-scale ear images dataset in the wild
title_fullStr EarVN1.0: A new large-scale ear images dataset in the wild
title_full_unstemmed EarVN1.0: A new large-scale ear images dataset in the wild
title_sort earvn1.0: a new large-scale ear images dataset in the wild
publisher Elsevier
series Data in Brief
issn 2352-3409
publishDate 2019-12-01
description Ear recognition is starting to grow as an alternative to other biometric recognition types in recent years. The EarVN1.0 dataset is constructed by collecting ear images of 164 Asian peoples during 2018. It is among the largest ear datasets publicly to the research community which composed by 28,412 colour images of 98 males and 66 females. Thus, this dataset is different from previous works by providing images of both ears per person under unconstrained conditions. The original facial images have been acquired by unconstrained environment including cameras systems and light condition. Ear images are then cropped from facial images over the large variations of pose, scale and illumination. Several machine learning tasks can be applied such as ear recognition, image classification or clustering, gender recognition, right-ear or left-ear detection and enhanced super resolution. Keywords: Ear recognition, Biometric, Image classification, Super-resolution, Image clustering, Right-ear or left-ear detection
url http://www.sciencedirect.com/science/article/pii/S2352340919309850
work_keys_str_mv AT vinhtruonghoang earvn10anewlargescaleearimagesdatasetinthewild
_version_ 1725051741998678016