TELKOMNIKA Telecommunication, Computing, Electronics and Control
Face recognition based on curvelets, invariant moments features and SVM
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Face recognition based on curvelets, invariant moments features and SVM
Face recognition based on curvelets, invariant moments features and SVM
Subject
Curvelet, Face recognition, Invariant moment, Support vector machine
Description
Recent studies highlighted on face recognition methods. In this paper, a new algorithm is proposed for face recognition by combining Fast Discrete Curvelet Transform (FDCvT) and Invariant Moments with Support vector machine (SVM), which improves rate of face recognition in various situations. The reason of using this approach depends on two things. first, Curvelet transform which is a multi-resolution method, that can efficiently represent image edge discontinuities; Second, the Invariant Moments analysis which is a statistical method that meets with the translation, rotation and scale invariance in the image. Furthermore, SVM is employed to classify the face image based on the extracted features. This process is applied on each of ORL and Yale databases to evaluate the performance of the suggested method. Experimentally, the proposed method results show that our system can compose efficient and reasonable face recognition feature, and obtain useful recognition accuracy, which is able to face and side-face states detection of persons to decrease fault rate of production.
Creator
Mohammed Talal Ghazal, Karam Abdullah
Source
DOI: 10.12928/TELKOMNIKA.v18i2.14106
Publisher
Universitas Ahmad Dahlan
Date
April 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Mohammed Talal Ghazal, Karam Abdullah, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Face recognition based on curvelets, invariant moments features and SVM,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3672.
Face recognition based on curvelets, invariant moments features and SVM,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3672.