TELKOMNIKA Telecommunication, Computing, Electronics and Control
Adaptive threshold for moving objects detection using gaussian mixture model
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Adaptive threshold for moving objects detection using gaussian mixture model
Adaptive threshold for moving objects detection using gaussian mixture model
Subject
Detection, Gaussian mixture model, Moving object, Otsu, Threshold
Description
Moving object detection becomes the important task in the video surveilance system. Defining the threshold automatically is challenging to differentiate the moving object from the background within a video. This study proposes gaussian mixture model (GMM) as a threshold strategy in moving object detection. The performance of the proposed method is compared to the Otsu algorithm and gray threshold as the baseline method using mean square error (MSE) and Peak Signal Noise Ratio (PSNR). The performance comparison of the methods is evaluated on human video dataset. The average result of MSE value GMM is 257.18, Otsu is 595.36 and Gray is 645.39, so the MSE value is lower than Otsu and Gray threshold. The average result of PSNR value GMM is 24.71, Otsu is 20.66 and Gray is 19.35, so the PSNR value is higher than Otsu and Gray threshold. The performance of the proposed method
outperforms the baseline method in term of error detection.
outperforms the baseline method in term of error detection.
Creator
Moch Arief Soeleman, Aris Nurhindarto, Muslih, Karis W., Muljono, Farikh Al Zami, R. Anggi Pramunendar
Source
DOI: 10.12928/TELKOMNIKA.v18i2.14878
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
Moch Arief Soeleman, Aris Nurhindarto, Muslih, Karis W., Muljono, Farikh Al Zami, R. Anggi Pramunendar , “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Adaptive threshold for moving objects detection using gaussian mixture model,” Repository Horizon University Indonesia, accessed November 22, 2024, https://repository.horizon.ac.id/items/show/3729.
Adaptive threshold for moving objects detection using gaussian mixture model,” Repository Horizon University Indonesia, accessed November 22, 2024, https://repository.horizon.ac.id/items/show/3729.