Validation of Tool Mark Comparisons Obtained Using a Quantitative, Comparative, Statistical Algorithm
Abstract
Abstract: A statistical analysis and computational algorithm for comparing pairs of tool marks via profilometry data is described. Empirical validation of the method is established through experiments based on tool marks made at selected fixed angles from 50 sequentially manufactured screwdriver tips. Results obtained from three different comparison scenarios are presented and are in agreement with experiential knowledge possessed by practicing examiners. Further comparisons between scores produced by the algorithm and visual assessments of the same tool mark pairs by professional tool mark examiners in a blind study in general show good agreement between the algorithm and human experts. In specific instances where the algorithm had difficulty in assessing a particular comparison pair, results obtained during the collaborative study with professional examiners suggest ways in which algorithm performance may be improved. It is concluded that the addition of contextual information when inputting data into the algorithm should result in better performance.
Citing Literature
Number of times cited according to CrossRef: 30
- Martin Baiker-Sørensen, Koen Herlaar, Isaac Keereweer, Petra Pauw-Vugts, Richard Visser, The forensic examination of marks review: 2016 to 2018, Forensic Science International: Synergy, 10.1016/j.fsisyn.2020.01.016, (2020).
- Erwin J.A.T. Mattijssen, Cilia L.M. Witteman, Charles E.H. Berger, Nicolaas W. Brand, Reinoud D. Stoel, Validity and reliability of forensic firearm examiners, Forensic Science International, 10.1016/j.forsciint.2019.110112, 307, (110112), (2020).
- References, Forensic Firearm Examination, 10.1016/B978-0-12-814539-5.00022-8, (305-312), (2019).
- Zhe Chen, Wei Chu, Johannes A. Soons, Robert M. Thompson, John Song, Xuezeng Zhao, Fired Bullet Signature Correlation Using the Congruent Matching Profile Segments (CMPS) Method, Forensic Science International, 10.1016/j.forsciint.2019.109964, (109964), (2019).
- Min Yang, Li Mou, Yi‐Ming Fu, Yu Wang, Jiang‐feng Wang, Quantitative Statistics and Identification of Tool‐Marks, Journal of Forensic Sciences, 10.1111/1556-4029.14040, 64, 5, (1324-1334), (2019).
- Ganesh Krishnan, Heike Hofmann, Adapting the Chumbley Score to Match Striae on Land Engraved Areas (LEAs) of Bullets, , Journal of Forensic Sciences, 10.1111/1556-4029.13950, 64, 3, (728-740), (2018).
- Ronald Nichols, The examination process, Firearm and Tool Mark Identification, 10.1016/B978-0-12-813250-0.00005-X, (73-91), (2018).
- Ronald Nichols, State of the art, Firearm and Tool Mark Identification, 10.1016/B978-0-12-813250-0.00004-8, (51-71), (2018).
- A. Sandras, C. Guilbeau-Frugier, F. Savall, N. Telmon, C. Capuani, Sharp bone trauma diagnosis: a validation study using epifluorescence microscopy, International Journal of Legal Medicine, 10.1007/s00414-018-1944-z, (2018).
- Jeremy R. Hadler, Max D. Morris, An Improved Version of a Tool Mark Comparison Algorithm, Journal of Forensic Sciences, 10.1111/1556-4029.13640, 63, 3, (849-855), (2017).
- Pierre Duez, Todd Weller, Marcus Brubaker, Richard E. Hockensmith, Ryan Lilien, Development and Validation of a Virtual Examination Tool for Firearm Forensics, , , Journal of Forensic Sciences, 10.1111/1556-4029.13668, 63, 4, (1069-1084), (2017).
- Li Mou, Min Yang, Cheng-Zhong Zhan, Yi-Ming Fu, undefined, 2017 2nd International Conference on Multimedia and Image Processing (ICMIP), 10.1109/ICMIP.2017.31, (22-26), (2017).
- Manuel Keglevic, Robert Sablatnig, Retrieval of striated toolmarks using convolutional neural networks, IET Computer Vision, 10.1049/iet-cvi.2017.0161, 11, 7, (613-619), (2017).
- John E. Murdock, Nicholas D.K. Petraco, John I. Thornton, Michael T. Neel, Todd J. Weller, Robert M. Thompson, James E. Hamby, Eric R. Collins, The Development and Application of Random Match Probabilities to Firearm and Toolmark Identification, Journal of Forensic Sciences, 10.1111/1556-4029.13386, 62, 3, (619-625), (2017).
- Scott Chumbley, Song Zhang, Max Morris, Ryan Spotts, Chad Macziewski, Development of a Mobile Toolmark Characterization/Comparison System, Journal of Forensic Sciences, 10.1111/1556-4029.13233, 62, 1, (83-91), (2016).
- Chad Macziewski, Ryan Spotts, Scott Chumbley, Validation of Toolmark Comparisons Made At Different Vertical and Horizontal Angles, Journal of Forensic Sciences, 10.1111/1556-4029.13342, 62, 3, (612-618), (2016).
- Tasha P. Smith, G. Andrew Smith, Jeffrey B. Snipes, A Validation Study of Bullet and Cartridge Case Comparisons Using Samples Representative of Actual Casework, Journal of Forensic Sciences, 10.1111/1556-4029.13093, 61, 4, (939-946), (2016).
- Martin Baiker, Nicholas D.K. Petraco, Carol Gambino, René Pieterman, Peter Shenkin, Peter Zoon, Virtual and simulated striated toolmarks for forensic applications, Forensic Science International, 10.1016/j.forsciint.2016.01.035, 261, (43-52), (2016).
- Ryan Spotts, L. Scott Chumbley, Laura Ekstrand, Song Zhang, James Kreiser, Angular Determination of Toolmarks Using a Computer‐Generated Virtual Tool, Journal of Forensic Sciences, 10.1111/1556-4029.12759, 60, 4, (878-884), (2015).
- Ryan Spotts, L. Scott Chumbley, Objective Analysis of Impressed Chisel Toolmarks, Journal of Forensic Sciences, 10.1111/1556-4029.12863, 60, 6, (1436-1440), (2015).
- Martin Baiker, René Pieterman, Peter Zoon, Toolmark variability and quality depending on the fundamental parameters: Angle of attack, toolmark depth and substrate material, Forensic Science International, 10.1016/j.forsciint.2015.03.003, 251, (40-49), (2015).
- Ryan Spotts, L. Scott Chumbley, Laura Ekstrand, Song Zhang, James Kreiser, Optimization of a Statistical Algorithm for Objective Comparison of Toolmarks, Journal of Forensic Sciences, 10.1111/1556-4029.12642, 60, 2, (303-314), (2014).
- Laura Ekstrand, Song Zhang, Taylor Grieve, L. Scott Chumbley, M. James Kreiser, Virtual Tool Mark Generation for Efficient Striation Analysis, , Journal of Forensic Sciences, 10.1111/1556-4029.12435, 59, 4, (950-959), (2014).
- Martin Baiker, Isaac Keereweer, René Pieterman, Erwin Vermeij, Jaap van der Weerd, Peter Zoon, Quantitative comparison of striated toolmarks, Forensic Science International, 10.1016/j.forsciint.2014.06.038, 242, (186-199), (2014).
- George Gerules, Sanjiv K. Bhatia, Daniel E. Jackson, A survey of image processing techniques and statistics for ballistic specimens in forensic science, Science & Justice, 10.1016/j.scijus.2012.07.002, 53, 2, (236-250), (2013).
- Amy B. Lock, Max D. Morris, Significance of Angle in the Statistical Comparison of Forensic Tool Marks, Technometrics, 10.1080/00401706.2013.851626, 55, 4, (548-561), (2013).
- S.G. Bunch, Laboratory Analysis, Encyclopedia of Forensic Sciences, 10.1016/B978-0-12-382165-2.00268-3, (136-141), (2013).
- Caroline Capuani, Jacques Rouquette, Bruno Payré, Jacques Moscovici, Marie Bernadette Delisle, Norbert Telmon, Céline Guilbeau-Frugier, Deciphering the elusive nature of sharp bone trauma using epifluorescence macroscopy: a comparison study multiplexing classical imaging approaches, International Journal of Legal Medicine, 10.1007/s00414-012-0678-6, 127, 1, (169-176), (2012).
- V. Heikkinen, I. Kassamakov, E. Haggstrom, S. Lehto, J. Kiljunen, T. Reinikainen, J. Aaltonen, undefined, 2011 IEEE International Conference on Technologies for Homeland Security (HST), 10.1109/THS.2011.6107892, (332-337), (2011).
- Carol Gambino, Patrick McLaughlin, Loretta Kuo, Frani Kammerman, Peter Shenkin, Peter Diaczuk, Nicholas Petraco, James Hamby, Nicholas D. K. Petraco, Forensic surface metrology: tool mark evidence, Scanning, 10.1002/sca.20251, 33, 5, (272-278), (2011).




