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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Jurnal Rekayasa elektrika
Oktiana, Maulisa
Universitas Syiah Kuala
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Features for Cross Spectral Image Matching: A Survey Maulisa Oktiana; Fitri Arnia; Yuwaldi Away; Khairul Munadi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (533.461 KB) | DOI: 10.11591/eei.v7i4.843

Abstract

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.
Features for Cross Spectral Image Matching: A Survey Maulisa Oktiana; Fitri Arnia; Yuwaldi Away; Khairul Munadi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v7i4.843

Abstract

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.
Features for Cross Spectral Image Matching: A Survey Maulisa Oktiana; Fitri Arnia; Yuwaldi Away; Khairul Munadi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (532.648 KB) | DOI: 10.11591/eei.v7i4.843

Abstract

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.
Identifikasi Tingkat Kematangan Kelapa Sawit Berbasis Pencitraan Termal Khusnul Azima; Khairul Munadi; Fitri Arnia; Maulisa Oktiana
Jurnal Rekayasa Elektrika Vol 15, No 1 (2019)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1469.872 KB) | DOI: 10.17529/jre.v15i1.12963

Abstract

Indonesia is the biggest producer of palm oil (Elaeis guineenis jacq).  The palm tree is a primary commodity that posses a high economic value. Palm oil must be considered in terms of quality to produce optimal and high-quality oil. Previously, the stipulation of the palm tree characterization used manual and visual image utilization method; it may have weaknesses due to the dependency of individual sorting and coruscation factor. Therefore, this research is aimed to improve the performance of the previous method in identifying the ripeness of palm tree based on thermal imaging. The excess of thermal imaging was not related to the coruscation since the level of ripeness was both determined by the temperature and colour. The detection method of this research deployed the colour-based features that are Dominant Colour Descriptor and Color Moment. The DCD  and Color Moment was the input to the K-Nearest Neighbor (KNN) method.  The percentage of identification rate was 89%, and the identification of oil palm maturity level using thermal imaging is more efficient because it is done without human intervention and does not depend on lighting assistance compared to manual method and method of using RGB visual images.
Identifikasi Tingkat Kematangan Kelapa Sawit Berbasis Pencitraan Termal Khusnul Azima; Khairul Munadi; Fitri Arnia; Maulisa Oktiana
Jurnal Rekayasa Elektrika Vol 15, No 1 (2019)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v15i1.12963

Abstract

Indonesia is the biggest producer of palm oil (Elaeis guineenis jacq).  The palm tree is a primary commodity that posses a high economic value. Palm oil must be considered in terms of quality to produce optimal and high-quality oil. Previously, the stipulation of the palm tree characterization used manual and visual image utilization method; it may have weaknesses due to the dependency of individual sorting and coruscation factor. Therefore, this research is aimed to improve the performance of the previous method in identifying the ripeness of palm tree based on thermal imaging. The excess of thermal imaging was not related to the coruscation since the level of ripeness was both determined by the temperature and colour. The detection method of this research deployed the colour-based features that are Dominant Colour Descriptor and Color Moment. The DCD  and Color Moment was the input to the K-Nearest Neighbor (KNN) method.  The percentage of identification rate was 89%, and the identification of oil palm maturity level using thermal imaging is more efficient because it is done without human intervention and does not depend on lighting assistance compared to manual method and method of using RGB visual images.
Co-Authors Fitri Arnia Fitri Arnia Khairul Munadi Khairul Munadi Khusnul Azima Yuwaldi Away