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Open AccessFeature PaperArticle

Ear Detection and Localization with Convolutional Neural Networks in Natural Images and Videos

Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced S/N, 37008 Salamanca, Spain
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Processes 2019, 7(7), 457; https://doi.org/10.3390/pr7070457
Received: 18 June 2019 / Revised: 5 July 2019 / Accepted: 11 July 2019 / Published: 17 July 2019
(This article belongs to the Special Issue Bioinformatics Applications Based On Machine Learning)
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Abstract

The difficulty in precisely detecting and locating an ear within an image is the first step to tackle in an ear-based biometric recognition system, a challenge which increases in difficulty when working with variable photographic conditions. This is in part due to the irregular shapes of human ears, but also because of variable lighting conditions and the ever changing profile shape of an ear’s projection when photographed. An ear detection system involving multiple convolutional neural networks and a detection grouping algorithm is proposed to identify the presence and location of an ear in a given input image. The proposed method matches the performance of other methods when analyzed against clean and purpose-shot photographs, reaching an accuracy of upwards of 98%, but clearly outperforms them with a rate of over 86% when the system is subjected to non-cooperative natural images where the subject appears in challenging orientations and photographic conditions. View Full-Text
Keywords: ear detection; computer vision; convolutional neural network; image recognition; video analysis ear detection; computer vision; convolutional neural network; image recognition; video analysis
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Raveane, W.; Galdámez, P.L.; González Arrieta, M.A. Ear Detection and Localization with Convolutional Neural Networks in Natural Images and Videos. Processes 2019, 7, 457.

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