DocumentCode
1613954
Title
Firearm identification using numerical features of centre firing pin impression image
Author
Ghani, Nor Azura Md ; Kamaruddin, S.B.A. ; Choong-Yeun Liong ; Jemain, Abdul Aziz
Author_Institution
Center for Stat. Studies & Decision Sci., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear
2012
Firstpage
293
Lastpage
296
Abstract
There are many crime cases such as murders or robberies which frequently involve firearms, especially pistols. The centre firing pin impression image on a cartridge case is one of the important clues for firearms identification. In this study, a total of 16 features of geometric moments up to the sixth order were extracted from centre of firing pin impression images. A total of five pistols of the Parabellum Vector SPI 9mm model, made in South Africa were used. The pistols were labelled as Pistol A, Pistol B, Pistol C, Pistol D, and Pistol E. A total of 747 bullets have been fired from the five pistols. Under preliminary analysis, Pearson correlation coefficients between all pairs of features showed the features were significant and highly correlated among the features. This problematic features were solved by dividing the features into subgroups of variables based on similar characteristics under principle component analysis. The features that highly correlated were combined into meaningful components or factors. Discriminant analysis was applied to identify the types of pistols used based on the factors obtained. Classification results using cross-validation under discriminant analysis showed that 75.4% of the images were correctly classified according to the pistols used. The results of the study had shown a significant contribution towards Royal Malaysian Police Force in handling crime cases which involve firearms in more systematic manner.
Keywords
image classification; principal component analysis; weapons; Parabellum vector SPI 9mm model; Pearson correlation coefficient; Royal Malaysian Police Force; South Africa; bullets; cartridge case; centre firing pin impression image; crime cases; discriminant analysis; firearm identification; numerical features; pistols; principle component analysis; Computer applications; Educational institutions; Eigenvalues and eigenfunctions; Feature extraction; Firing; Forensics; Industrial electronics; discriminant analysis; firearm identification; firing pin impression; geometric moment; principle component analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Applications and Industrial Electronics (ISCAIE), 2012 IEEE Symposium on
Conference_Location
Kota Kinabalu
Print_ISBN
978-1-4673-3032-9
Type
conf
DOI
10.1109/ISCAIE.2012.6482115
Filename
6482115
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