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...

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Bibliographic Details
Published in:Data in brief 2019-12, Vol.27, p.104630-104630, Article 104630
Main Author: Hoang, Vinh Truong
Format: Article
Language:English
Subjects:
Biometric
Computer Science
Ear recognition
Image classification
Image clustering
Right-ear or left-ear detection
Super-resolution
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Summary: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.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2019.104630