Ballistics Image Processing and Analysis for Firearm Identification

The identification of firearms from forensic ballistics specimens is an exacting and intensive activity performed by specialists with extensive experience. The introduction of imaging technology to assist the identification process of firearms has enhanced the ability of forensic ballisticians to conduct analyses of these specimens for identification. The positive identification of ballistics specimens from imaging systems are important applications of technology in criminal investigation [1] [2] [3] [4]. While the image capture methodology for persons and forensic ballistics specimens is similar, the process of identification for each is dependent upon the level of certainty required for the identification. The forensic identification of ballistics specimens relies on the detection, recognition and ultimate matching of markings on the surfaces of cartridges and projectiles made by the firearms [5]. Traditional methods for the comparison of these marks are based on incident light microscopy. The image formed from the oblique illumination of the mark gives a representation of the surface of the specimen in the region of the mark [6]. This representation is critically dependent on the material of the surface on which the marks have been made, and the geometry and intensity of the illumination system. The assessment by the ballistician of the similarity between comparable marks on respective ballistics specimens from crime scenes and test firings will be based on the expertise and experience of the technologist. Thus the traditional method of matching markings has inherent difficulties, and entails an element of subjectivity [7]. The need for firearm identification systems by police services continues to increase with greater accessibility to weapons in the international contexts. The characteristic markings on the cartridge and projectile of a bullet fired from a gun can be recognized as a fingerprint for identification of the firearm [8]. Forensic ballistics imaging has the capacity to produce highresolution digital images of cartridge cases and projectiles for matching to a library of ballistics images [9]. However, the reliance upon imaging technologies makes identification of ballistics specimens both a demanding and exacting task, where the control of the error of

[1]  Max Robinson,et al.  Validation of the linescan imaging technique for imaging cylindrical forensic ballistics specimens , 2004 .

[2]  Sung-Bae Cho,et al.  Pattern recognition with neural networks combined by genetic algorithm , 1999, Fuzzy Sets Syst..

[3]  Clifton L. Smith,et al.  Ballistics identification using line-scan imaging techniques , 1997, Proceedings IEEE 31st Annual 1997 International Carnahan Conference on Security Technology.

[4]  Jpo Evans,et al.  Line-scan imaging using an area array camera , 1998 .

[5]  Ioannis Pitas,et al.  Parallel Algorithms for Digital Image Processing, Computer Vision and Neural Networks , 1993 .

[6]  Jun Kong,et al.  A Firearm Identification System Based on Neural Network , 2003, Australian Conference on Artificial Intelligence.

[7]  Eliot Springer,et al.  Toolmark Examinations—A Review of Its Development in the Literature , 1995 .

[8]  Horst Bunke,et al.  Off-Line, Handwritten Numeral Recognition by Perturbation Method , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Clifton L. Smith,et al.  Optical imaging techniques for ballistics specimens to identify firearms , 1995, Proceedings The Institute of Electrical and Electronics Engineers. 29th Annual 1995 International Carnahan Conference on Security Technology.

[10]  Ponnuthurai Nagaratnam Suganthan.  Structure adaptive multilayer overlapped SOMs with supervision for handprinted digit classification , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

[11]  E. F. Pearson.  Forensic Science Handbook , 1983 .

[12]  Gerald Burrard.  The Identification of Firearms and Forensic Ballistics , 1956 .

[13]  Teuvo Kohonen,et al.  In: Self-organising Maps , 1995 .

[14]  Cheng-Tan Tung,et al.  FISOFM: firearms identification based on SOFM model of neural network , 1994, 1994 Proceedings of IEEE International Carnahan Conference on Security Technology.

[15]  Max Robinson,et al.  Line-scan imaging for the positive identification of ballistics specimens , 2000, Proceedings IEEE 34th Annual 2000 International Carnahan Conference on Security Technology (Cat. No.00CH37083).

[16]  Gang Rong,et al.  A cartridge identification system for firearm authentication , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[17]  R. Ghauharali,et al.  Visualisation by confocal microscopy of traces on bullets and cartridge cases. , 2000, Science & justice : journal of the Forensic Science Society.

[18]  R. Nichols,et al.  Firearm and Toolmark Identification Criteria: A Review of the Literature , 1997 .

[19]  Pragya Agarwal,et al.  Self-Organising Maps , 2008 .

[20]  Rudolf Kingslake,et al.  Optics in photography , 1992 .

[21]  Bunch.  Consecutive matching striation criteria: a general critique , 2000, Journal of forensic sciences.

[22]  Andrew W. Fitzgibbon,et al.  Direct least squares fitting of ellipses , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[23]  Ioannis Pitas,et al.  Digital Image Processing Algorithms , 1993 .

[24]  Dongguang Li,et al.  Ballistics firearms identification based on images of a cartridge case and projectile , 1998, Other Conferences.

[25]  Clifton L. Smith.  Fireball: a forensic ballistics imaging system , 1997, Proceedings IEEE 31st Annual 1997 International Carnahan Conference on Security Technology.

[26]  Clifton L. Smith.  Linescan imaging of ballistics projectile markings for identification , 2002, Proceedings. 36th Annual 2002 International Carnahan Conference on Security Technology.

[27]  Clifton Smith.  Profile measurements as a technique for forensic ballistics identification , 2001 .