Human face recognition by Euclidean distance and neural network
The idea of this project development is to improve the concept of human face recognition that has been studied in order to apply it for a more precise and effective recognition of human faces, and offered an alternative to agencies with respect to their access-departure control system. To accomplish...
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th-mahidol.290242018-09-24T16:45:15Z Human face recognition by Euclidean distance and neural network Chomtip Pornpanomchai Chittrapol Inkuna Mahidol University Computer Science Engineering Materials Science Mathematics Physics and Astronomy The idea of this project development is to improve the concept of human face recognition that has been studied in order to apply it for a more precise and effective recognition of human faces, and offered an alternative to agencies with respect to their access-departure control system. To accomplish this, a technique of calculation of distances between face features, including efficient face recognition though a neural network, is used. The system uses a technique of image processing consisting of 3 major processes: 1) preprocessing or preparation of images, 2) feature extraction from images of eyes, ears, nose and mouth, used for a calculation of Euclidean distances between each organ; and 3) face recognition using a neural network method. Based on the experimental results from reading image of a total of 200 images from 100 human faces, the system can correctly recognize 96 % with average access time of 3.304 sec per image. © 2010 Copyright SPIE - The International Society for Optical Engineering. 2018-09-24T08:57:43Z 2018-09-24T08:57:43Z 2010-03-22 Conference Paper Proceedings of SPIE - The International Society for Optical Engineering. Vol.7546, (2010) 10.1117/12.852248 0277786X 2-s2.0-77949461425 https://repository.li.mahidol.ac.th/handle/123456789/29024 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77949461425&origin=inward |
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Computer Science Engineering Materials Science Mathematics Physics and Astronomy Chomtip Pornpanomchai Chittrapol Inkuna Human face recognition by Euclidean distance and neural network |
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The idea of this project development is to improve the concept of human face recognition that has been studied in order to apply it for a more precise and effective recognition of human faces, and offered an alternative to agencies with respect to their access-departure control system. To accomplish this, a technique of calculation of distances between face features, including efficient face recognition though a neural network, is used. The system uses a technique of image processing consisting of 3 major processes: 1) preprocessing or preparation of images, 2) feature extraction from images of eyes, ears, nose and mouth, used for a calculation of Euclidean distances between each organ; and 3) face recognition using a neural network method. Based on the experimental results from reading image of a total of 200 images from 100 human faces, the system can correctly recognize 96 % with average access time of 3.304 sec per image. © 2010 Copyright SPIE - The International Society for Optical Engineering. |
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Mahidol University |
author_facet |
Mahidol University Chomtip Pornpanomchai Chittrapol Inkuna |
format |
Conference or Workshop Item |
author |
Chomtip Pornpanomchai Chittrapol Inkuna |
author_sort |
Chomtip Pornpanomchai |
title |
Human face recognition by Euclidean distance and neural network |
title_short |
Human face recognition by Euclidean distance and neural network |
title_full |
Human face recognition by Euclidean distance and neural network |
title_fullStr |
Human face recognition by Euclidean distance and neural network |
title_full_unstemmed |
Human face recognition by Euclidean distance and neural network |
title_sort |
human face recognition by euclidean distance and neural network |
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2018 |
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https://repository.li.mahidol.ac.th/handle/123456789/29024 |
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1763487364617863168 |