Human recognition based on multi-instance ear scheme.

Ear biometrics is one of the primary biometrics that is definitely standing out. Ear recognition enjoys special benefits and can make distinguishing proof safer and dependable along with other biometrics (for example fingerprints and face). Particularly as a supplement to face recognition schemes th...

Full description

Saved in:
Bibliographic Details
Main Authors: Hussein, Inass Sh., Sjarif, Nilam Nur Amir
Format: Article
Language:English
Published: Research Institute of Intelligent Computer Systems 2023
Subjects:
Online Access:http://eprints.utm.my/105539/1/InassShHussein2023_HumanRecognitionBasedonMultiInstaneEarScheme.pdf
http://eprints.utm.my/105539/
http://dx.doi.org/10.47839/ijc.22.3.3236
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.105539
record_format eprints
spelling my.utm.1055392024-05-05T06:27:26Z http://eprints.utm.my/105539/ Human recognition based on multi-instance ear scheme. Hussein, Inass Sh. Sjarif, Nilam Nur Amir TA Engineering (General). Civil engineering (General) Ear biometrics is one of the primary biometrics that is definitely standing out. Ear recognition enjoys special benefits and can make distinguishing proof safer and dependable along with other biometrics (for example fingerprints and face). Particularly as a supplement to face recognition schemes that experience issues in genuine circumstances. This is because of the extraordinary variety of a planar representation of a confusing object that is varied in shapes, illumination, and profile shape. This study is an endeavor to conquer these restrictions, by proposing scaleinvariant feature transform (SIFT) calculation to extract feature vector descriptors from both left and right ears which is to be melded as one descriptor utilized for verification purposes. Likewise, another plan is proposed for the recognition stage, based on a genetic algorithm-backpropagation neural network as an accurate recognition approach. This approach will be tried by utilizing images from the Indian Institute of Technology Delhi's creation (IITD). The suggested system exhibits a 99.7% accuracy recognition rate. Research Institute of Intelligent Computer Systems 2023-02-20 Article PeerReviewed application/pdf en http://eprints.utm.my/105539/1/InassShHussein2023_HumanRecognitionBasedonMultiInstaneEarScheme.pdf Hussein, Inass Sh. and Sjarif, Nilam Nur Amir (2023) Human recognition based on multi-instance ear scheme. International Journal of Computing, 22 (3). pp. 397-403. ISSN 1727-6209 http://dx.doi.org/10.47839/ijc.22.3.3236 DOI: 10.47839/ijc.22.3.3236
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Hussein, Inass Sh.
Sjarif, Nilam Nur Amir
Human recognition based on multi-instance ear scheme.
description Ear biometrics is one of the primary biometrics that is definitely standing out. Ear recognition enjoys special benefits and can make distinguishing proof safer and dependable along with other biometrics (for example fingerprints and face). Particularly as a supplement to face recognition schemes that experience issues in genuine circumstances. This is because of the extraordinary variety of a planar representation of a confusing object that is varied in shapes, illumination, and profile shape. This study is an endeavor to conquer these restrictions, by proposing scaleinvariant feature transform (SIFT) calculation to extract feature vector descriptors from both left and right ears which is to be melded as one descriptor utilized for verification purposes. Likewise, another plan is proposed for the recognition stage, based on a genetic algorithm-backpropagation neural network as an accurate recognition approach. This approach will be tried by utilizing images from the Indian Institute of Technology Delhi's creation (IITD). The suggested system exhibits a 99.7% accuracy recognition rate.
format Article
author Hussein, Inass Sh.
Sjarif, Nilam Nur Amir
author_facet Hussein, Inass Sh.
Sjarif, Nilam Nur Amir
author_sort Hussein, Inass Sh.
title Human recognition based on multi-instance ear scheme.
title_short Human recognition based on multi-instance ear scheme.
title_full Human recognition based on multi-instance ear scheme.
title_fullStr Human recognition based on multi-instance ear scheme.
title_full_unstemmed Human recognition based on multi-instance ear scheme.
title_sort human recognition based on multi-instance ear scheme.
publisher Research Institute of Intelligent Computer Systems
publishDate 2023
url http://eprints.utm.my/105539/1/InassShHussein2023_HumanRecognitionBasedonMultiInstaneEarScheme.pdf
http://eprints.utm.my/105539/
http://dx.doi.org/10.47839/ijc.22.3.3236
_version_ 1800082626138079232
score 13.211869