Scanning baggage by x-ray and analysing such images have become important technique for detecting
illicit materials in the baggage at Airports. In order to provide adequate security, a reliable and fast
screening technique is needed for baggage examination.This paper aims at providing an automatic method
for detecting concealed weapons, typically a gun in the baggage by employing image segmentation method
to extract the objects of interest from the image followed by applying feature extraction methods namely
Shape context descriptor and Zernike moments. Finally the objects are classified using fuzzy KNN as illicit
or non-illicit object.
%0 Journal Article
%1 noauthororeditor
%A Roomi, Dr. Mohamed Mansoor
%A R.Rajashankari,
%D 2012
%J International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)
%K Aviation Classifier Context Descriptor Moments Nearest Neighbour Shape Zernike security
%N 2
%P 187-196
%R 10.5121/ijcseit.2012.2216
%T DETECTION OF CONCEALED WEAPONS IN X-RAY
IMAGES USING FUZZY K-NN
%U http://airccse.org/journal/ijcseit/papers/2212ijcseit16.pdf
%V 2
%X Scanning baggage by x-ray and analysing such images have become important technique for detecting
illicit materials in the baggage at Airports. In order to provide adequate security, a reliable and fast
screening technique is needed for baggage examination.This paper aims at providing an automatic method
for detecting concealed weapons, typically a gun in the baggage by employing image segmentation method
to extract the objects of interest from the image followed by applying feature extraction methods namely
Shape context descriptor and Zernike moments. Finally the objects are classified using fuzzy KNN as illicit
or non-illicit object.
@article{noauthororeditor,
abstract = {Scanning baggage by x-ray and analysing such images have become important technique for detecting
illicit materials in the baggage at Airports. In order to provide adequate security, a reliable and fast
screening technique is needed for baggage examination.This paper aims at providing an automatic method
for detecting concealed weapons, typically a gun in the baggage by employing image segmentation method
to extract the objects of interest from the image followed by applying feature extraction methods namely
Shape context descriptor and Zernike moments. Finally the objects are classified using fuzzy KNN as illicit
or non-illicit object. },
added-at = {2018-07-27T11:05:51.000+0200},
author = {Roomi, Dr. Mohamed Mansoor and R.Rajashankari},
biburl = {https://www.bibsonomy.org/bibtex/28f17f7c11c86eff893f5299f9b47428b/ijcseit},
doi = {10.5121/ijcseit.2012.2216},
interhash = {348f94f8dddca2afb54bf70633ac1113},
intrahash = {8f17f7c11c86eff893f5299f9b47428b},
issn = {2231-3117 [Online] ; 2231-3605 [Print]},
journal = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)},
keywords = {Aviation Classifier Context Descriptor Moments Nearest Neighbour Shape Zernike security},
language = {English},
month = apr,
number = 2,
pages = {187-196},
timestamp = {2018-07-27T11:05:51.000+0200},
title = {DETECTION OF CONCEALED WEAPONS IN X-RAY
IMAGES USING FUZZY K-NN},
url = {http://airccse.org/journal/ijcseit/papers/2212ijcseit16.pdf},
volume = 2,
year = 2012
}