Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat

In this paper we evaluate and discuss the application of Legendre orthogonal moments (LOMs) as features for recognition of passenger positions that have been segmented using local thresholding technique. Identification of passenger position in a car is vital in a smart-car system; for example, id...

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Main Authors: Choong-Yeun Liong, Chris Thompson, Yuan-Chiu Teo
Format: Article
Published: Penerbit ukm 2008
Online Access:http://journalarticle.ukm.my/1882/
http://journalarticle.ukm.my/1882/
id ukm-1882
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spelling ukm-18822011-06-16T03:45:13Z http://journalarticle.ukm.my/1882/ Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat Choong-Yeun Liong, Chris Thompson, Yuan-Chiu Teo, In this paper we evaluate and discuss the application of Legendre orthogonal moments (LOMs) as features for recognition of passenger positions that have been segmented using local thresholding technique. Identification of passenger position in a car is vital in a smart-car system; for example, identifying the passenger position may help in intelligent deployment of the safety airbags. In this study, a total of 1292 images of ten different classes of passenger position have been used. These images have been segmented using the local thresholding technique in order to separate the passenger region from the image background. Then nine LOMs features have been generated for each of the segmented images. The segmentation and feature extraction tasks have been accomplished using C++ programs. The moment features were then fed into the SPSS package for classification using discriminant analysis. The importance of each of the moments in its ability to explain each of the positions is also investigated. The classification results show that 99.5% of the data has been classified successfully. The applicability of the local thresholding technique for the segmentation task is well supported by this very high success rate. We can conclude that the passenger position images investigated has been very well discriminated into the desired passenger position classes. This suggests that the application of local thresholding technique and LOMs is a potential choice for the identification of the various passenger positions Penerbit ukm 2008-12 Article PeerReviewed Choong-Yeun Liong, and Chris Thompson, and Yuan-Chiu Teo, (2008) Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat. Journal of Quality Measurement and Analysis, 4 (2). pp. 81-99. ISSN 1823-5670 http://www.ukm.my/~ppsmfst/jqma/index.html
repository_type Digital Repository
institution_category Local University
institution Universiti Kebangasaan Malaysia
building UKM Institutional Repository
collection Online Access
description In this paper we evaluate and discuss the application of Legendre orthogonal moments (LOMs) as features for recognition of passenger positions that have been segmented using local thresholding technique. Identification of passenger position in a car is vital in a smart-car system; for example, identifying the passenger position may help in intelligent deployment of the safety airbags. In this study, a total of 1292 images of ten different classes of passenger position have been used. These images have been segmented using the local thresholding technique in order to separate the passenger region from the image background. Then nine LOMs features have been generated for each of the segmented images. The segmentation and feature extraction tasks have been accomplished using C++ programs. The moment features were then fed into the SPSS package for classification using discriminant analysis. The importance of each of the moments in its ability to explain each of the positions is also investigated. The classification results show that 99.5% of the data has been classified successfully. The applicability of the local thresholding technique for the segmentation task is well supported by this very high success rate. We can conclude that the passenger position images investigated has been very well discriminated into the desired passenger position classes. This suggests that the application of local thresholding technique and LOMs is a potential choice for the identification of the various passenger positions
format Article
author Choong-Yeun Liong,
Chris Thompson,
Yuan-Chiu Teo,
spellingShingle Choong-Yeun Liong,
Chris Thompson,
Yuan-Chiu Teo,
Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
author_facet Choong-Yeun Liong,
Chris Thompson,
Yuan-Chiu Teo,
author_sort Choong-Yeun Liong,
title Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
title_short Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
title_full Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
title_fullStr Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
title_full_unstemmed Pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
title_sort pengecaman kedudukan penumpang menggunakan momen ortogon legendre dan teknik pengambangan setempat
publisher Penerbit ukm
publishDate 2008
url http://journalarticle.ukm.my/1882/
http://journalarticle.ukm.my/1882/
first_indexed 2023-09-18T19:34:34Z
last_indexed 2023-09-18T19:34:34Z
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