Pilot study of feature-based algorithm for breech face comparison

Zhang, Hao; Gu, Jialiang; Chen, Jin; Sun, Fuzhong; Wang, Hua

doi:10.1016/j.forsciint.2018.02.026

Cited by 10 publications

(4 citation statements)

References 17 publications

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“…Then, roughness surface (Figure 3) can be extracted via point‐by‐point subtraction between the measured topography and mean surface. The purpose here is to extract the critical micro‐geometries representing the individual characteristics from the macro‐geometries (size, shape, and waviness) representing the class characteristics of certain brands of firearms for better automated analysis [2].…”

Section: Methodsmentioning

confidence: 99%

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Convergence‐improved congruent matching cells (CMC) method for firing pin impression comparison

Zhang

Zhu

Hong

et al. 2020

Journal of Forensic Sciences

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A firing pin impression is usually concave in shape with a small textured area, which makes it difficult to perform automated algorithm‐based comparison. The congruent matching cells (CMC) method was invented for accurate breech face impression comparison, in which a reference impression is divided into correlation cells. Each cell is registered to a cell‐sized area of the comparison impression that has maximum similarity in surface topography. Four parameters are used to quantify the congruent matching pattern of the registration position and orientation. This paper aims to further develop the cell‐division‐matching method based on a convergence feature and to develop practical convergence‐improved algorithms for firing pin impression comparison. The convergence feature refers to the tendency of the x‐y registration positions of correlated cell pairs to converge at the correct registration angle when comparing same‐source samples at different orientations. The areal Gaussian filter is employed to extract high‐frequency micro‐features; the least‐squares matching method is used to improve each cross‐correlation precision and reach convergence in the registration positions of correlated cell pairs; and a density‐based clustering algorithm is introduced to collect the registration positions of dense cell pairs relative to a virtual common center and to remove outliers. Improvements are achieved in the reliability and accuracy of the number of congruent matching cell pairs (CMCs) collected, which represents the quantification of the degree of pairwise impression similarity. Experiments in this report used 40 firing pin impression samples on cartridge cases fired from 10 pistols. The results included no false identifications or false exclusions.

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Section: Methodsmentioning

confidence: 99%

“…These form a kind of toolmark called “ballistic signatures” [1]. In ballistic examinations, these signatures are compared in detail to assess whether the bullets or casings were fired from a particular firearm [2].…”

Section: Introductionmentioning

confidence: 99%

Convergence‐improved congruent matching cells (CMC) method for firing pin impression comparison

Zhang

Zhu

Hong

et al. 2020

Journal of Forensic Sciences

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“…An interesting study was proposed by Zhang et al [39], which exploited the combination of two algorithms: SIFT (Scale Invariant Feature Transform) and RANSAC (RANdom SAmple Consensus) applied to the breech face impression. The SIFT algorithm was used for the extraction key points and to compute its descriptors.…”

Section: Related Workmentioning

confidence: 99%

Assessing forensic ballistics three-dimensionally through graphical reconstruction and immersive VR observation

Guarnera

Giudice

Livatino

et al. 2022

Multimed Tools Appl

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A crime scene can provide valuable evidence critical to explain reason and modality of the occurred crime, and it can also lead to the arrest of criminals. The type of evidence collected by crime scene investigators or by law enforcement may accordingly effective involved cases. Bullets and cartridge cases examination is of paramount importance in forensic science because they may contain traces of microscopic striations, impressions and markings, which are unique and reproducible as “ballistic fingerprints”. The analysis of bullets and cartridge cases is a complicated and challenging process, typically based on optical comparison, leading to the identification of the employed firearm. New methods have recently been proposed for more accurate comparisons, which rely on three-dimensionally reconstructed data. This paper aims at further advancing recent methods by introducing a novel immersive technique for ballistics comparison by means of Virtual Reality. Users can three-dimensionally examine the cartridge cases shapes through intuitive natural gestures, from any vantage viewpoint (including internal iper-magnified views), while having at their disposal sets of visual aids which could not be easily implemented in desktop-based applications. A user study was conducted to assess viability and performance of our solution, which involved fourteen individuals acquainted with the standard procedures used by law enforcement agencies. Results clearly indicated that our approach lead to faster adaptation of users to the UI/UX and more accurate and explainable ballistics examination results.

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“…An algorithm would first evaluate the topography data of each surface that will be compared and identify features, which are typically peaks and valleys with a distinct lateral position. 48,49 The score is the ratio of similar features whose difference in location can be explained by the rotation and translation of the compared surface. The advantage of this featurebased scoring method is that once the features are identified, the evaluation of this number or ratio of similar features can be done extremely fast, making this method well suited for database searches and mimicking how a human examiner would compare two exemplars.…”

Section: Computer-aided Firearm and Toolmark Analysismentioning

confidence: 99%

2022 Firearm and Toolmarks Policy and Practice Forum

2022

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The National Institute of Justice (NIJ) and the Forensic Technology Center of Excellence, an NIJ program hosted a four-day symposium, January 11–14, 2022. The symposium included presentations and panel discussions on topics relevant to recent advances in firearm and toolmark examination with a focus on the future. The symposium brought together 685 criminal justice processionals to explore implementation of three-dimensional (3D) imaging technologies, best practices for forensic examination of firearm and toolmark evidence, federal initiatives, gun crime intelligence, black box studies on firearm and toolmark examination, legal challenges to the admissibility of current examination of firearm and toolmark evidence and engineering solutions that will be used in court in the future, implementation of Organization of Scientific Area Committee (OSAC) standards and reporting, uniform language in testimony and conclusion scales. The panel discussions and presentations and provided examples of how agencies implement new imaging technologies for firearms and toolmark examination, incorporate statistics to add weight to forensic comparisons, address legal issues, and operationalize forensic intelligence to improve public safety and share information with the justice community. The symposium also provided a platform to discuss a series of considerations for the forensic, law enforcement, and greater criminal justice community that could help support a successful national transition to incorporate statistics in forensic testimony and accelerate the adoption of imaging technologies for firearm and toolmark examination.

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Pilot study of feature-based algorithm for breech face comparison

Cited by 10 publications

References 17 publications

Convergence‐improved congruent matching cells (CMC) method for firing pin impression comparison

Convergence‐improved congruent matching cells (CMC) method for firing pin impression comparison

Assessing forensic ballistics three-dimensionally through graphical reconstruction and immersive VR observation

2022 Firearm and Toolmarks Policy and Practice Forum

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