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Face recognition technique based on artificial neural network and principal component analysis
Joint Authors
Batti, Nur Hamdi
al-Hamami, Ala Husayn
Source
International Computer Sciences and Informatics Conference, Amman, Jordan 12-13 January 2016.
Publisher
Publication Date
2016-01-31
Country of Publication
Jordan
No. of Pages
13
Main Subjects
Information Technology and Computer Science
English Abstract
This research will use data mining (DM) algorithm and principle component analysis (PCA) to extract features from images by using Eigen vector function.
Data mining and PCA are the process of finding correlations or patterns in the images then take these image features to neural network for training and testing.
Image pre-processing is required prior to presenting the training or testing images to the neural network.
This process is to reduce the computational cost and providing a faster recognition system while presenting the neural network with sufficient data representation of each face to achieve meaningful learning.
At the end, the attained outcomes from the tests will be demonstrated and analyzed, which these tests are based on colored pictures with one face background.
A comparison will be done to relate works with proposed algorithm to accomplish good precision.
Data Type
Conference Papers
Record ID
BIM-767266
American Psychological Association (APA)
al-Hamami, Ala Husayn& Batti, Nur Hamdi. 2016-01-31. Face recognition technique based on artificial neural network and principal component analysis. . , pp.39-51.Amman Jordan : Amman Arab University.
https://search.emarefa.net/detail/BIM-767266
Modern Language Association (MLA)
al-Hamami, Ala Husayn& Batti, Nur Hamdi. Face recognition technique based on artificial neural network and principal component analysis. . Amman Jordan : Amman Arab University. 2016-01-31.
https://search.emarefa.net/detail/BIM-767266
American Medical Association (AMA)
al-Hamami, Ala Husayn& Batti, Nur Hamdi. Face recognition technique based on artificial neural network and principal component analysis. .
https://search.emarefa.net/detail/BIM-767266