Three-dimensional surface reconstruction for cartridge cases using photometric stereo

In forensic science, automated firearms identification is an important and yet unsolved problem. On the way to the solution, one of the most important phases is data acquisition. To be able to identify firearms in a reliable way, all the striated and impressed marks on metallic surfaces of cartridge cases should be visible. But two-dimensional images of cartridge cases are very sensitive to the type and direction of the light source(s). Depending on illumination conditions, the images of marks change drastically and sometimes they simply disappear. But, if the three-dimensional (3D) topography of the surface is obtained, the geometry of the marks, which is independent of the illumination, is available. Thus, by providing illumination independent features that can be used for automated matching, 3D data have the potential to make automated matching much reliable. In the literature on data acquisition for automated firearms identification, a few different ways of three-dimensional surface extraction are described, like laser interferometry or laser profilometry. This study presents a real life application of another method, photometric stereo, for the acquisition of 3D topographic data for cartridge cases, which is the one used in BALISTIKA Ballistics Image Analysis and Recognition System. In order to construct 3D topographic data, first of all, two-dimensional images were acquired using a specially designed set-up. After the images were calibrated radiometrically, photometric stereo method was applied. In order to minimize the low-frequency errors in the final surface, a surface-fitting algorithm was used. The method uses low-cost equipment and image acquisition is not time-consuming. Results were compared to interferometric measurement values for error assessment.     

Statistical Approaches to Type Determination of the Ejector Marks on Cartridge Cases

While type determination on bullets has been performed for over a century, type determination on cartridge cases is often overlooked. Presented here is an example of type determination of ejector marks on cartridge cases from Glock and Smith & Wesson Sigma series pistols using Naïve Bayes and Random Forest classification methods. The shapes of ejector marks were captured from images of test‐fired cartridge cases and subjected to multivariate analysis. Naïve Bayes and Random Forest methods were used to assign the ejector shapes to the correct class of firearm with success rates as high as 98%. This method is easily implemented with equipment already available in crime laboratories and can serve as an investigative lead in the form of a list of firearms that could have fired the evidence. Paired with the FBI's General Rifling Characteristics (GRC) database, this could be an invaluable resource for firearm evidence at crime scenes.     

Classification of firing pin impressions using HOG-SVM

Crimes, such as robbery and murder, often involve firearms. In order to assist with the investigation into the crime, firearm examiners are asked to determine whether cartridge cases found at a crime scene had been fired from a suspect's firearm. This examination is based on a comparison of the marks left on the surfaces of cartridge cases. Firing pin impressions can be one of the most commonly used of these marks. In this study, a total of nine Ruger model 10/22 semiautomatic rifles were used. Fifty cartridges were fired from each rifle. The cartridge cases were collected, and each firing pin impression was then cast and photographed using a comparison microscope. In this paper, we will describe how one may use a computer vision algorithm, the Histogram of Orientated Gradient (HOG), and a machine learning method, Support Vector Machines (SVMs), to classify images of firing pin impressions. Our method achieved a reasonably high accuracy at 93%. This can be used to associate a firearm with a cartridge case recovered from a scene. We also compared our method with other feature extraction algorithms. The comparison results showed that the HOG-SVM method had the highest performance in this classification task.     

Evaluation of GLOCK 9 mm Firing Pin Aperture Shear Mark Individuality Based On 1,632 Different Pistols by Traditional Pattern Matching and IBIS Pattern Recognition

Over a period of 21 years, a number of fired GLOCK cartridge cases have been evaluated. A total of 1632 GLOCK firearms were used to generate a sample of the same size. Our research hypothesis was that no cartridge cases fired from different 9‐mm semiautomatic GLOCK pistols would be mistaken as coming from the same gun. Using optical comparison microscopy, two separate experiments were carried out to test this hypothesis. A subsample of 617 test‐fired cases were subjected to algorithmic comparison by the Integrated Ballistics Identification System (IBIS). The second experiment subjected the full set of 1632 cases to manual comparisons using traditional pattern matching. None of the cartridge cases were “matched” by either of these two experiments. Using these empirical findings, an established Bayesian probability model was used to estimate the chance that a 9‐mm cartridge case, fired from a GLOCK, could be mistaken as coming from the same firearm when in fact it did not (i.e., the random match probability).     

Reference ballistic imaging database performance

Ballistic imaging databases allow law enforcement to link recovered cartridge cases to other crime scenes and to firearms. The success of these databases has led many to propose that all firearms in circulation be entered into a reference ballistic image database (RBID). To assess the performance of an RBID, we fired 4200 cartridge cases from 600 9 mm Para Sig Sauer model P226 series pistols. Each pistol fired two Remington cartridges, one of which was imaged in the RBID, and five additional cartridges, consisting of Federal, Speer, Winchester, Wolf, and CCI brands. Randomly selected samples from the second series of Remington cartridge cases and from the five additional brands were then correlated against the RBID. Of the 32 cartridges of the same make correlated against the RBID, 72% ranked in the top 10 positions. Likewise, of the 160 cartridges of the five different brands correlated against the database, 21% ranked in the top 10 positions. Generally, the ranking position increased as the size of the RBID increased. We obtained similar results when we expanded the RBID to include firearms with the same class characteristics for breech face marks, firing pin impressions, and extractor marks. The results of our six queries against the RBID indicate that a reference ballistics image database of new guns is currently fraught with too many difficulties to be an effective and efficient law enforcement tool.     

Reference ballistic imaging database performance

Ballistic imaging databases allow law enforcement to link recovered cartridge cases to other crime scenes and to firearms. The success of these databases has led many to propose that all firearms in circulation be entered into a reference ballistic image database (RBID). To assess the performance of an RBID, we fired 4200 cartridge cases from 600 9mm Para Sig Sauer model P226 series pistols. Each pistol fired two Remington cartridges, one of which was imaged in the RBID, and five additional cartridges, consisting of Federal, Speer, Winchester, Wolf, and CCI brands. Randomly selected samples from the second series of Remington cartridge cases and from the five additional brands were then correlated against the RBID. Of the 32 cartridges of the same make correlated against the RBID, 72% ranked in the top 10 positions. Likewise, of the 160 cartridges of the five different brands correlated against the database, 21% ranked in the top 10 positions. Generally, the ranking position increased as the size of the RBID increased. We obtained similar results when we expanded the RBID to include firearms with the same class characteristics for breech face marks, firing pin impressions, and extractor marks. The results of our six queries against the RBID indicate that a reference ballistics image database of new guns is currently fraught with too many difficulties to be an effective and efficient law enforcement tool.     

79式微型冲锋枪子弹射击顺序的研究

目的研究79式微型冲锋枪发射子弹的排序。方法对已知顺序实弹射击取样,扩大观察弹头、弹壳上发射过程中形成的痕迹,通过统计、归纳,从中发现与排序有关的痕迹特征。结果壳体肩部圆点痕,弹底边缘压擦痕、拉壳钩痕与发射顺序有关。结论壳体肩部圆点痕、弹底边缘压擦痕等痕迹的有无、位置及轻重程度,对判断79式微型冲锋枪弹壳发射顺序有较可靠的参考价值。     

Characteristics and dynamics of illegal firearms markets: Implications for a supply-side enforcement strategy

The question of whether the illegal firearms market serving criminals and juveniles can be disrupted has been vigorously debated. Recent research suggests that illegal gun markets consist of both “point sources” (ongoing diversions through scofflaw dealers and trafficking rings) and “diffuse sources” (acquisitions through theft and informal, voluntary sales). To the extent that systematic gun trafficking is an important source of weapons for criminals and youth, focused regulatory and investigative resources may be effective in disrupting the illegal flow. In this research, we use data on traced firearms to examine one aspect of the illegal gun market that holds the most immediate promise for focused supply-side enforcement efforts—close-to-retail diversions. We find that almost one-third of traceable crime guns were recently diverted from legitimate retail firearms commerce and that nearly one-third had two or more indicators of gun trafficking involving dealers, purchasers, and possessors. We discuss the implications of these findings for understanding illegal gun markets and for developing effective supply-side enforcement strategies.     

Reactivating deactivated firearms

Deactivating firearms necessitates a certain number of modifications to the firearm. We will show how in a number of cases these modifications were overcome. The material of which we dispose makes it possible to see what were the subsequent steps in the reactivation of the firearms. Inherently to their hand craft nature, very characteristic marks are obtained for the cartridge cases.     

Pistol image retrieval by shape representation

Databases have been used to record data in forensic science, such as fingerprints, shoeprints, and photos. In traditional databases, we use “text” as the “keyword” for retrieving data (text-keyword retrieval); however, in some applications, “text” is not proper to describe the searching target, and in this case, “image” plays an important role. In this paper, we use “image features” as the “keywords”, and show its potential for building up a prototype of pistol image databases.In current firearm databases of forensic science, the retrieval method is still by text-keyword retrieval. For experienced forensic examiners, this kind of databases may satisfy their requirement. However, for people who have little gun knowledge, how can they find the possible gun candidates or similar guns in the databases, if there are not any available words or marks on the gun? In this paper, we try to retrieve similar pistol images by the pistol shape instead of “text-keyword”. This method can narrow down the searching range while identifying pistols by firearm databases.There are more than 300 pistol images in our pistol image database. From the experimental results, we can retrieve the similar pistol images in top five candidates for each pistol image.     

Identification of a Suspect in a Murder Case through Recovery of Fingermarks from a Fired Cartridge Case

During the period of one year, the Police of the State of Espírito Santo in Brazil analyzed 1,431 cartridge cases obtained from crime scenes and seizures. The cartridges were subjected to a development sequence (cyanoacrylate fuming + gun bluing + fluorescent dying), and panoramic images of the developed fingermarks were generated based on the photographs taken during the rotation of the cartridges. Ridge details were observed in 50 cartridges, but only in 5 cartridges, the marks were considered with value for identification. The fingermarks were searched in the Automated Fingerprint Identification System (AFIS) of the Brazilian Federal Police and, in one case, it was possible to obtain the suspect's identification. In our knowledge, this is the first case in Brazil of identification of a suspect based on a fingermark recovered from a fired cartridge case.     

Challenge of Firearms Control in a Free Society

Chapter 10 of The Challenge of Crime in a Free Society, titled “Control of Firearms,” is a brief but strong statement in support of regulating gun transactions, possession, and carrying, with several specific recommendations, including the adoption of universal gun registration and permit‐to‐purchase requirements. The U.S. President's Commission on Law Enforcement and Administration of Justice, when writing the chapter, had no systematic research to draw on. Since its publication in 1967, the field of gun violence has become an active area of research, and much has been learned. But the nation has become far more polarized politically during the last 50 years, and gun policy has become a rigidly partisan issue. A new commission would have great difficulty reaching consensus, although there may be common ground on regulating guns vis‐à‐vis mental illness and domestic violence.     

Visualisation by confocal microscopy of traces on bullets and cartridge cases

The capabilities of confocal scanning laser microscopy for the visualisation of marks on bullets and cartridge cases were investigated. Confocal microscopy provides solutions to important limitations of conventional comparison microscopy with grazing light incidence, as generally used for the examination of these marks. It is expected that confocal microscopy, thanks to its broad applicability within the field of firearms investigation and its capability of non-destructively gathering quantitative three-dimensional information, will lead to a more complete and objective forensic examination of bullets and cartridge cases.     

Automated detection of regions of interest in cartridge case images using deep learning

This paper explores a deep-learning approach to evaluate the position of circular delimiters in cartridge case images. These delimiters define two regions of interest (ROI), corresponding to the breech face and the firing pin impressions, and are placed manually or by an image-processing algorithm. This positioning bears a significant impact on the performance of the image-matching algorithms for firearm identification, and an automated evaluation method would be beneficial to any computerized system. Our contribution consists in optimizing and training U-Net segmentation models from digital images of cartridge cases, intending to locate ROIs automatically. For the experiments, we used high-resolution 2D images from 1195 samples of cartridge cases fired by different 9MM firearms. Our results show that the segmentation models, trained on augmented data sets, exhibit a performance of 95.6% IoU (Intersection over Union) and 99.3% DC (Dice Coefficient) with a loss of 0.014 for the breech face images; and a performance of 95.9% IoU and 99.5% DC with a loss of 0.011 for the firing pin images. We observed that the natural shapes of predicted circles reduce the performance of segmentation models compared with perfect circles on ground truth masks suggesting that our method provide a more accurate segmentation of the real ROI shape. In practice, we believe that these results could be useful for firearms identification. In future work, the predictions may be used to evaluate the quality of delimiters on specimens in a database, or they could determine the region of interest on a cartridge case image.     

Image matching algorithms for breech face marks and firing pins in a database of spent cartridge cases of firearms

On the market several systems exist for collecting spent ammunition data for forensic investigation. These databases store images of cartridge cases and the marks on them. Image matching is used to create hit lists that show which marks on a cartridge case are most similar to another cartridge case. The research in this paper is focused on the different methods of feature selection and pattern recognition that can be used for optimizing the results of image matching.The images are acquired by side light images for the breech face marks and by ring light for the firing pin impression. For these images a standard way of digitizing the images used. For the side light images and ring light images this means that the user has to position the cartridge case in the same position according to a protocol. The positioning is important for the sidelight, since the image that is obtained of a striation mark depends heavily on the angle of incidence of the light. In practice, it appears that the user positions the cartridge case with +/-10 degrees accuracy.We tested our algorithms using 49 cartridge cases of 19 different firearms, where the examiner determined that they were shot with the same firearm. For testing, these images were mixed with a database consisting of approximately 4900 images that were available from the Drugfire database of different calibers.In cases where the registration and the light conditions among those matching pairs was good, a simple computation of the standard deviation of the subtracted gray levels, delivered the best-matched images. For images that were rotated and shifted, we have implemented a "brute force" way of registration. The images are translated and rotated until the minimum of the standard deviation of the difference is found. This method did not result in all relevant matches in the top position. This is caused by the effect that shadows and highlights are compared in intensity. Since the angle of incidence of the light will give a different intensity profile, this method is not optimal.For this reason a preprocessing of the images was required. It appeared that the third scale of the "à trous" wavelet transform gives the best results in combination with brute force. Matching the contents of the images is less sensitive to the variation of the lighting.The problem with the brute force method is however that the time for calculation for 49 cartridge cases to compare between them, takes over 1 month of computing time on a Pentium II-computer with 333MHz. For this reason a faster approach is implemented: correlation in log polar coordinates. This gave similar results as the brute force calculation, however it was computed in 24h for a complete database with 4900 images.A fast pre-selection method based on signatures is carried out that is based on the Kanade Lucas Tomasi (KLT) equation. The positions of the points computed with this method are compared. In this way, 11 of the 49 images were in the top position in combination with the third scale of the à trous equation. It depends however on the light conditions and the prominence of the marks if correct matches are found in the top ranked position. All images were retrieved in the top 5% of the database. This method takes only a few minutes for the complete database if, and can be optimized for comparison in seconds if the location of points are stored in files.For further improvement, it is useful to have the refinement in which the user selects the areas that are relevant on the cartridge case for their marks. This is necessary if this cartridge case is damaged and other marks that are not from the firearm appear on it.     

A part-declared blind testing program in firearms examination

In 2015 and 2016 the Central Unit of the Dutch National Police created and submitted 21 cartridge case comparison tests as real cases to the Netherlands Forensic Institute (NFI), under supervision of the University of Twente (UT). A total of 53 conclusions were drawn in these 21 tests. For 31 conclusions the underlying ground truth was “positive”, in the sense that it addressed a cluster of cartridge cases that was fired from the same firearm. For 22 conclusions the ground truth was “negative”, in the sense that the cartridge cases were fired from different firearms. In none of the conclusions, resulting from examinations under casework conditions, misleading evidence was reported. All conclusions supported the hypothesis reflecting the ground truth. This article discusses the design and results of the tests in more detail.     

Objective Evaluation of Subclass Characteristics on Breech Face Marks

Subclass characteristics can be found on the breech face marks left on spent cartridge cases. Even if they are assumed to be rare and their reported number is small, they can potentially lead to false associations. Subclass characteristics have been studied empirically allowing examiners to recognize them and to understand in which conditions they are produced. Until now, however, their influence on the identification process has not been studied from a probabilistic point of view. In this study, we aim at measuring the effect of these features on the strength of association derived from examinations involving subclass characteristics. The study takes advantage of a 3D automatic comparison system allowing the calculation of likelihood ratios (LRs). The similarities between cartridge case specimens fired by thirteen S&W .40S&W Sigma pistols are quantified, and their respective LRs are computed. The results show that the influence of subclass characteristics on the LRs is limited, even when these features are prevalent among the potential sources considered in a case. We show that the proportion of firearms sharing subclass characteristics should be larger than 40% of the pool of potential firearms for the effect to be significant.     

A Validation Study of Bullet and Cartridge Case Comparisons Using Samples Representative of Actual Casework

The foundation of firearm and tool mark identification is that no two tools should produce the same microscopic marks on two separate objects that they would be inaccurately or wrongly identified. Studies addressing the validity of identification infrequently employ tests that mirror realistic casework scenarios. This study attempted to do so using a double‐blind process, reducing test‐taking bias. Test kits including bullets and cartridge cases but not the associated firearms were completed by 31 analysts from 22 agencies. Analysis of the results demonstrated an overall error rate of 0.303%, sensitivity of 85.2%, and specificity of 86.8%. Variability in performance across examiners is addressed, and the effect of examiners’ years of experience on identification accuracy is explored. Finally, the article discusses the importance of studies using realistic case work scenarios when validating the field's performance and in providing courts with usable indicators of the accuracy of firearm and tool mark identification.     

Automated region segmentation on cartridge case base

One of the significant problems encountered in criminology studies is the successful automated matching of fired cartridge cases, on the basis of the characteristic marks left on them by firearms. An intermediate step in the solution of this problem is the segmentation of certain regions that are defined on the cartridge case base. This paper describes a model-based method that performs segmentation of the cartridge case using surface height image of a center fire cartridge case base. The proposed method detects the location of the cartridge case base center and specific circular contours around it iteratively by projecting the problem to a one-dimensional feature space. In addition, the firing pin impression region is determined by utilizing an adaptive threshold that differentiates impression marks form primer region surface. Letters on the cartridge case base are also detected by using surface modeling and adaptive thresholding, in order to render the surface comparison operation robust against irrelevant surface features. Promising experimental results indicate the eligibility of the proposed method to be used for automated cartridge case base region segmentation process.     

Understanding Suicide Across the Lifespan: A United States Perspective of Suicide Risk Factors,Assessment & Management

Suicide is a troubling, preventable phenomenon. Prior to attempts, individuals often seek help, prompting practitioners to perform risk assessments that ideally use evidence‐based risk management strategies. A literature review was performed using Harvard Countway Library of Medicine, Google Scholar, PubMed. Key words used were “Forensic Science,” “Suicide Risk Management,” “Pediatric Suicide Risk Factors,” “Adult Suicide Risk Factors,” “Geriatric Suicide Risk Factors,” “Suicide Risk Assessment.” Parameters limited articles to studies/reviews completed in the past twenty years in the United States. Results indicated predictors of suicide in juveniles were insomnia, burdensomeness, and recent conflicts with family or a romantic partner. Adults had greater risk if male, substance abusing, with marital/job loss. Elderly individuals with multiple medical comorbidities, hopelessness, and isolation were at higher risk. Everyone evaluated should be screened for access to firearms. Management of suicide risk involves providing the least restrictive form of treatment which maintains an individual's safety.