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Combination of fast hybrid classification and k value optimization in k-nn for video face recognition

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Title Combination of fast hybrid classification and k value optimization in k-nn for video face recognition
 
Creator Septiana, Nuning
Suciati, Nanik
 
Subject face recognition; Fast Hybrid Classification; k-NN; video
 
Description Nowadays, the need for face recognition is no longer include images only but also videos. However, there are some challenges associated with the addition of this new technique such as how to determine the right pre-processing, feature extraction, and classification methods to obtain excellent performance. Although nowadays the k-Nearest Neighbor (k-NN) is widely used, high computational costs due to numerous features of the dataset and large amount of training data makes adequate processing difficult. Several studies have been conducted to improve the performance of k-NN using the FHC (Fast Hybrid Classification) method by optimizing the local k values. One of the disadvantages of the FHC Method is that the k value used is still in the default form. Therefore, this research proposes the use of k-NN value optimization methods in FHC, thereby, increasing its accuracy. The Fast Hybrid Classification which combines the k-means clustering with k-NN, groups the training data into several prototypes called TLDS (Two Level Data Structure). Furthermore, two classification levels are applied to label test data, with the first used to determine the n number of prototypes with the same class in the test data. The second classification using the optimized k value in the k-NN method, is employed to sharpen the accuracy, when the same number of prototypes does not reach n. The evaluation results show that this method provides 86% accuracy and time performance of 3.3 seconds.
 
Publisher Information Systems - Universitas Pesantren Tinggi Darul Ulum
 
Contributor —
 
Date 2020-04-06
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://journal.unipdu.ac.id/index.php/register/article/view/1668
10.26594/register.v6i1.1668
 
Source Register: Jurnal Ilmiah Teknologi Sistem Informasi; Vol 6, No 1 (2020): January; 65-73
Register: Jurnal Ilmiah Teknologi Sistem Informasi; Vol 6, No 1 (2020): January; 65-73
2502-3357
2503-0477
10.26594/register.v6i1
 
Language eng
 
Relation https://journal.unipdu.ac.id/index.php/register/article/view/1668/pdf
 
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