TELKOMNIKA Telecommunication, Computing, Electronics and Control
New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF)
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF)
New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF)
Subject
Face recognition, Feature matching, Four database, Normalization of feature, RANSAC with SURF, Recognition rate
Description
In recent years, facial recognition has been a major problem in the field
of computer vision, which has attracted lots of interest in previous years
because of its use in different applications by different domains and image analysis. Which is based on the extraction of facial descriptors, it is a very important step in facial recognition. In this article, we compared robust methods (SIFT, PCA-SIFT, ASIFT and SURF) to extract relevant facial information with different facial posture variations (open and unopened mouth, glasses and no glasses, open and closed eyes). The simulation results show that the detector (SURF) is better than others at finding the similarity descriptor and calculation time. Our method is based on the normalization of vector descriptors and combined with the RANSAC algorithm to cancel outliers in order to calculate the Hessian matrix with the objective of reducing the calculation time. To validate our experience, we tested four facial images databases containing several modifications. The results of the simulation show that our method is more efficient than other detectors in terms of speed of recognition and determination of similar points between two images of the same face, one belonging to the base of the text and the other one to the base driven by different modifications. This method, which can be applied on a mobile platform to analyze the content of simple images,
for example, to detect driver fatigue, human-machine interaction,
human-robot. Using descriptors with properties important for good accuracy and real-time response.
of computer vision, which has attracted lots of interest in previous years
because of its use in different applications by different domains and image analysis. Which is based on the extraction of facial descriptors, it is a very important step in facial recognition. In this article, we compared robust methods (SIFT, PCA-SIFT, ASIFT and SURF) to extract relevant facial information with different facial posture variations (open and unopened mouth, glasses and no glasses, open and closed eyes). The simulation results show that the detector (SURF) is better than others at finding the similarity descriptor and calculation time. Our method is based on the normalization of vector descriptors and combined with the RANSAC algorithm to cancel outliers in order to calculate the Hessian matrix with the objective of reducing the calculation time. To validate our experience, we tested four facial images databases containing several modifications. The results of the simulation show that our method is more efficient than other detectors in terms of speed of recognition and determination of similar points between two images of the same face, one belonging to the base of the text and the other one to the base driven by different modifications. This method, which can be applied on a mobile platform to analyze the content of simple images,
for example, to detect driver fatigue, human-machine interaction,
human-robot. Using descriptors with properties important for good accuracy and real-time response.
Creator
Ahmed Chater, Abdelali Lasfar
Source
DOI: 10.12928/TELKOMNIKA.v18i2.13726
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
Ahmed Chater, Abdelali Lasfar, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF),” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/3652.
New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF),” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/3652.