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...
Main Authors: | , , |
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Format: | Article |
Published: |
Penerbit ukm
2008
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Online Access: | http://journalarticle.ukm.my/1882/ http://journalarticle.ukm.my/1882/ |
Summary: | 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 |
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