Optimal compression and binarization of signature profiles for automated bullet identification systems

In some automated bullet identification systems, the similarity of striation marks between different bullets is measured using the cross correlation function of the compressed signature profile extracted from a land impression. Inclusion of invalid areas weakly striated by barrel features may lead to sub-optimal extraction of the signature profile and subsequent deterioration of correlation results. In this paper, a method for locating striation marks and selecting valid correlation areas based on an edge detection technique is proposed for the optimal extraction of the compressed signature profiles. Experimental results from correlating 48 bullets fired from 12 gun barrels of 6 manufacturers have demonstrated a higher correct matching rate than the previous study results without correlation area selection processing. Furthermore, an attempt to convert a traditional profile with multiple z-quantization (or gray scale) levels into a binary profile is made for the purpose of reducing storage space and increasing correlation speed.

[1]  Michael Heizmann.  Automated comparison of striation marks with the system GE/2 , 2002, SPIE Defense + Commercial Sensing.

[2]  Liam Blunt,et al.  Automated Bullet-Identification System Based on Surface Topography Techniques , 2009 .

[3]  J. Song,et al.  SRM 2460/2461 Standard Bullets and Casings Project , 2004, Journal of research of the National Institute of Standards and Technology.

[4]  Benjamin Bachrach,et al.  Development of a 3D-based automated firearms evidence comparison system. , 2002, Journal of forensic sciences.

[5]  Jan De Kinder,et al.  Automated comparisons of bullet striations based on 3D topography , 1999 .

[6]  Xiaoyu A. Zheng,et al.  Surface Topography Analysis for a Feasibility Assessment of a National Ballistics Imaging Database , 2012 .

[7]  Jun S. Huang,et al.  Statistical theory of edge detection , 1988, Comput. Vis. Graph. Image Process..

[8]  Kim L. Boyer,et al.  On Optimal Infinite Impulse Response Edge Detection Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Alan L. Yuille,et al.  A regularized solution to edge detection , 1985, J. Complex..

[10]  M. Bertero,et al.  Ill-posed problems in early vision , 1988, Proc. IEEE.

[11]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Wei Chu,et al.  Pilot Study of Automated Bullet Signature Identification Based on Topography Measurements and Correlations *† , 2010, Journal of forensic sciences.

[13]  Katsushi Ikeuchi,et al.  Three dimensional visualization and comparison of impressions on fired bullets. , 2004, Forensic science international.

[14]  Robert M. Thompson.  Automated firearms evidence comparison using the Integrated Ballistic Identification System (IBIS) , 1999, Other Conferences.