Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik

Firearms identification has been getting very important in crime investigation in the last two decades. In this paper, a recognition system for firearms identification based on cartridge case image is introduced. Cartridge case is one of the important clues towards solving the gun file. There are...

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Main Authors:	Nor Azura Md Ghani, Liong Choong-Yeun, Abdul Aziz Jemain
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2009
Online Access:	http://journalarticle.ukm.my/64/ http://journalarticle.ukm.my/64/ http://journalarticle.ukm.my/64/1/

id	ukm-64
recordtype	eprints
spelling	ukm-642016-12-14T06:26:18Z http://journalarticle.ukm.my/64/ Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik Nor Azura Md Ghani, Liong Choong-Yeun, Abdul Aziz Jemain, Firearms identification has been getting very important in crime investigation in the last two decades. In this paper, a recognition system for firearms identification based on cartridge case image is introduced. Cartridge case is one of the important clues towards solving the gun file. There are more than 30 marks left on the surface of the cartridge case when a gun is fired which are invaluable towards identifying the firearm used. These marks in combination produces a “fingerprint” for identification of a firearm. Therefore, the aim of this research work is towards extraction and identification of suitable features for firearms recognition. Firstly the cartridge case images are segmented into three parts, forming three sets of images. These images were also preprocessed to form three more sets of images. Features were extracted from these original and preprosessed. Twenty significant features each were identified and computed for the original and the preprocessed images. All processing were done using MATLAB programming. A scheme based on correlation analysis was introduced towards features selection based on the concept of minimising data redundancy but maximising classes’ differences. Features that are highly correlated were dropped and eventually there are only seven significant features. The seven features formed a feature vector for the fireams recognition and were tested on five pistols of the same model using discriminant analysis. The classification results show that more than 80% of the cartridge case images were classified correctly. Universiti Kebangsaan Malaysia 2009-04 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/64/1/ Nor Azura Md Ghani, and Liong Choong-Yeun, and Abdul Aziz Jemain, (2009) Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik. Sains Malaysiana, 38 (2). pp. 249-260. ISSN 0126-6039 http://www.ukm.my/~jsm/kandungan.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Firearms identification has been getting very important in crime investigation in the last two decades. In this paper, a recognition system for firearms identification based on cartridge case image is introduced. Cartridge case is one of the important clues towards solving the gun file. There are more than 30 marks left on the surface of the cartridge case when a gun is fired which are invaluable towards identifying the firearm used. These marks in combination produces a “fingerprint” for identification of a firearm. Therefore, the aim of this research work is towards extraction and identification of suitable features for firearms recognition. Firstly the cartridge case images are segmented into three parts, forming three sets of images. These images were also preprocessed to form three more sets of images. Features were extracted from these original and preprosessed. Twenty significant features each were identified and computed for the original and the preprocessed images. All processing were done using MATLAB programming. A scheme based on correlation analysis was introduced towards features selection based on the concept of minimising data redundancy but maximising classes’ differences. Features that are highly correlated were dropped and eventually there are only seven significant features. The seven features formed a feature vector for the fireams recognition and were tested on five pistols of the same model using discriminant analysis. The classification results show that more than 80% of the cartridge case images were classified correctly.
format	Article
author	Nor Azura Md Ghani, Liong Choong-Yeun, Abdul Aziz Jemain,
spellingShingle	Nor Azura Md Ghani, Liong Choong-Yeun, Abdul Aziz Jemain, Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
author_facet	Nor Azura Md Ghani, Liong Choong-Yeun, Abdul Aziz Jemain,
author_sort	Nor Azura Md Ghani,
title	Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
title_short	Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
title_full	Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
title_fullStr	Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
title_full_unstemmed	Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
title_sort	penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik
publisher	Universiti Kebangsaan Malaysia
publishDate	2009
url	http://journalarticle.ukm.my/64/ http://journalarticle.ukm.my/64/ http://journalarticle.ukm.my/64/1/
first_indexed	2023-09-18T19:01:09Z
last_indexed	2023-09-18T19:01:09Z
_version_	1777403082606379008

Penyaringan dan pemilihan fitur statistik asas untuk pengecaman spesimen forensik balistik

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