Form follows function: Applying photographic content analysis to forensic firearm identification

Drawing forensic conclusions from an image or a video is known as “photographic content analysis.” It involves the analysis of an image, as well as objects, actions, and events depicted in images or video. In recent years, photographic depictions of objects suspected as illegal firearms have substantially increased, appearing on CCTV surveillance footage, captured by mobile phones and shared on social media. However, the law in Israel states that a person can be charged with illegally possessing a firearm only if it can be proven that the object is capable of shooting with lethal bullet energy. This becomes more challenging in cases where the firearm was not physically seized, and the evidence exclusively consists of images and video. In this study, photographic content analysis was applied to images and video where objects suspected as commercial or improvised firearms had been depicted. An image and event sequence reconstruction video databases of both firearms and replicas were created in order to better define firearm-specific functional morphological features. We demonstrate that it is possible to classify an object as a firearm by analyzing the functional, and not only the esthetic, morphology in images and video. It is also shown that event sequence reconstruction in video may be used to infer that an object suspected as a firearm has the capacity to shoot by confirming the occurrence of a shooting act or shooting process. Thus, photographic content analysis may be used to forensically establish that an object depicted in an image or a video is a firearm by ruling out other known scenarios, and without physically seizing it.     

Shoeprint image retrieval and crime scene shoeprint image linking by using convolutional neural network and normalized cross correlation

A shoeprint image retrieval process aims to identify and match images of shoeprints found at crime scenes with shoeprint images from a known reference database. It is a challenging problem in the forensic discipline of footwear analysis because a shoeprint found at the crime scene is often imperfect. Recovered shoeprints may be partial, distorted, left on surfaces that do not mark easily, or perhaps come from shoes that do not transfer marks easily. In this study, we present a shoeprint retrieval method by using a convolutional neural network (CNN) and normalized cross-correlation (NCC). A pre-trained CNN was used to extract features from the pre-processed shoeprint images. We then employed NCC to compute a similarity score based on the extracted image features. We achieved a retrieval accuracy of 82% in our experiments, where a “successful” retrieval means that the ground truth image was returned in the top 1% of returned images. We also extend our shoeprint retrieval method to the problem of linking shoeprints recovered from crime scenes. This new method can provide a linkage between two crime scenes if the two recovered shoeprints originated from the same shoe. This new method achieved a retrieval accuracy of 88.99% in the top 20% of returned images.     

Content based information retrieval in forensic image databases

This paper gives an overview of the various available image databases and ways of searching these databases on image contents. The developments in research groups of searching in image databases is evaluated and compared with the forensic databases that exist. Forensic image databases of fingerprints, faces, shoeprints, handwriting, cartridge cases, drugs tablets, and tool marks are described. The developments in these fields appear to be valuable for forensic databases, especially that of the framework in MPEG-7, where the searching in image databases is standardized. In the future, the combination of the databases (also DNA-databases) and possibilities to combine these can result in stronger forensic evidence.     

High-speed search using Tarari content processor in digital forensics

Recently, “Speed” is one of the hot issues in digital forensics. Thanks to a recent advanced technology, today we can get bigger hard drive disks at a lower price than previously. But unfortunately, it means for forensic investigators that they need tremendous time and effort in the sequence of process of creating forensic images, searching into them and analyzing them. In order to solve this problem, some methods have been proposed to improve performance of forensic tools. One of them getting attention is a hardware-based approach. However, such a way is limited in the field of evidence cloning or password cracking while it is rarely used in searching and analysis of the digital evidence. In this paper, we design and implement a high-speed search engine using a Tarari content processor. Furthermore, we show feasibility of our approach by comparing its performance and features to those of a popular forensic tool currently on the market.     

High-speed search using Tarari content processor in digital forensics

Recently, “Speed” is one of the hot issues in digital forensics. Thanks to a recent advanced technology, today we can get bigger hard drive disks at a lower price than previously. But unfortunately, it means for forensic investigators that they need tremendous time and effort in the sequence of process of creating forensic images, searching into them and analyzing them. In order to solve this problem, some methods have been proposed to improve performance of forensic tools. One of them getting attention is a hardware-based approach. However, such a way is limited in the field of evidence cloning or password cracking while it is rarely used in searching and analysis of the digital evidence. In this paper, we design and implement a high-speed search engine using a Tarari content processor. Furthermore, we show feasibility of our approach by comparing its performance and features to those of a popular forensic tool currently on the market.     

Investigation of Ballistic Evidence through an Automatic Image Analysis and Identification System

Automated firearms identification (AFI) systems contribute to shedding light on criminal events by comparison between different pieces of evidence on cartridge cases and bullets and by matching similar ones that were fired from the same firearm. Ballistic evidence can be rapidly analyzed and classified by means of an automatic image analysis and identification system. In addition, it can be used to narrow the range of possible matching evidence. In this study conducted on the cartridges ejected from the examined pistol, three imaging areas, namely the firing pin impression, capsule traces, and the intersection of these traces, were compared automatically using the image analysis and identification system through the correlation ranking method to determine the numeric values that indicate the significance of the similarities. These numerical features that signify the similarities and differences between pistol makes and models can be used in groupings to make a distinction between makes and models of pistols.     

Multi-resolution image fusion technique and its application to forensic science

Image fusion is a process of combining two or more images into an image. It can extract features from source images, and provide more information than one image can. Multi-resolution analysis plays an important role in image processing, it provides a technique to decompose an image and extract information from coarse to fine scales. In some practical forensic examinations (such as the cartridge image check), we cannot obtain all information from just one image; on the contrary, we need information from images with difference light sources (or light ways). In this paper, we apply an image fusion method based on multi-resolution analysis to forensic science. Synthetic and real images (such as images from closed-up photography and flash photography) are used to show the capability of the multi-resolution image fusion technique.     

Multi-resolution image fusion technique and its application to forensic science

Image fusion is a process of combining two or more images into an image. It can extract features from source images, and provide more information than one image can. Multi-resolution analysis plays an important role in image processing, it provides a technique to decompose an image and extract information from coarse to fine scales. In some practical forensic examinations (such as the cartridge image check), we cannot obtain all information from just one image; on the contrary, we need information from images with difference light sources (or light ways). In this paper, we apply an image fusion method based on multi-resolution analysis to forensic science. Synthetic and real images (such as images from closed-up photography and flash photography) are used to show the capability of the multi-resolution image fusion technique.     

THE SOCIAL DETERMINANTS OF GUN OWNERSHIP: SELF-PROTECTION IN AN URBAN ENVIRONMENT*

Based on a survey of 539 residents of Cincinnati, this study assesses various explanations of gun ownership. The analysis reveals that gender and childhood socialization into a gun culture are significantly related to protective and general (or “sport”) firearm possession. In contrast, only protective gun ownership appears to be linked to crime-related factors. Conservative crime ideology and concern about the relative level of crime in one's neighborhood increase armament for defensive purposes, while informal collective security—the belief that neighbors will provide assistance against criminal victimization—reduces protective gun ownership.     

A Multimodal Fusion Approach for Bullet Identification Systems

In the field of forensic science, bullet identification is based on the fact that firing the cartridge from a barrel leaves exclusive microscopic striation on the fired bullets as the fingerprint of the firearm. The bullet identification methods are categorized in 2‐D and 3‐D based on their image acquisition techniques. In this study, we focus on 2‐D optical images using a multimodal technique and propose several distinct methods as its modalities. The proposed method uses a multimodal rule‐based linear weighted fusion approach which combines the semantic level decisions from different modalities with a linear technique that its optimized modalities weights have been identified by the genetic algorithm. The proposed approach was applied on a dataset, which includes 180 2‐D bullet images fired from 90 different AK‐47 barrels. The experimentations showed that our approach attained better results compared to common methods in the field of bullet identification.     

Warning behaviors and leaked intent: Potential new avenues to prevent mass shootings

On March 12, 2018, John Laubscher, owner of AJ’s Archery in Nelson, NY, had a gut feeling and refused to sell a rifle to a Syracuse University student—disrupting a mass shooting ( https://www.syracuse.com/crime/2018/04/how_gun_shop_owner_thwarted_on_the_edge_su_student_from_buying_high-capacity_rif.html . Accessed 10 Nov 2021). Prompted by this, we surveyed the opinions, beliefs, attitudes, and current practices of gun sellers in Onondaga County, NY, in regard to safe gun sales. The primary outcome was to determine which types of “concerning behaviors” are more likely to cause a seller to intervene in some manner. Secondary outcomes included the following: ascertaining the frequency of denials of customer purchases, frequency of reporting to law enforcement, and identifying any gaps that make it difficult for gun sellers to report behaviors to the authorities. Follow-up interviews were conducted with those who were willing to speak with the authors in more depth. A response rate of 12.9% was achieved. Sixty-two percent (62.5%) of respondents had some experience in uniformed services, with specialized training in mental or emotional crises, as well as deception detection. The majority found the training helpful in their gun selling career. Reasons for personal denials were reported as: “interest in illegal fittings,” “information revealed during conversation,” and “lack of basic knowledge of using the firearm looking to purchase.” Two respondents stated that due to a lack of a “reporting protocol,” they would not report any concerns to law enforcement. The study helps inform future research in regard to surveying more sellers across NY state and nationwide.     

A forensic science perspective on the role of images in crime investigation and reconstruction

This article presents a global vision of images in forensic science. The proliferation of perspectives on the use of images throughout criminal investigations and the increasing demand for research on this topic seem to demand a forensic science-based analysis. In this study, the definitions of and concepts related to material traces are revisited and applied to images, and a structured approach is used to persuade the scientific community to extend and improve the use of images as traces in criminal investigations. Current research efforts focus on technical issues and evidence assessment. This article provides a sound foundation for rationalising and explaining the processes involved in the production of clues from trace images. For example, the mechanisms through which these visual traces become clues of presence or action are described. An extensive literature review of forensic image analysis emphasises the existing guidelines and knowledge available for answering investigative questions (who, what, where, when and how). However, complementary developments are still necessary to demystify many aspects of image analysis in forensic science, including how to review and select images or use them to reconstruct an event or assist intelligence efforts. The hypothetico-deductive reasoning pathway used to discover unknown elements of an event or crime can also help scientists understand the underlying processes involved in their decision making. An analysis of a single image in an investigative or probative context is used to demonstrate the highly informative potential of images as traces and/or clues. Research efforts should be directed toward formalising the extraction and combination of clues from images. An appropriate methodology is key to expanding the use of images in forensic science.     

Suicidal Shotgun Wound Employing a Shotgun Barrel,a Shotgun Shell,and a BB*

Abstract: A vast majority of firearms‐related suicides involve the conventional use of a properly functioning, intact firearm. Occasionally, forensic investigators encounter a case wherein the firearm suicide victim employs some form of unconventional use of a weapon, or utilizes an unusual weapon type. In this case report, the authors present an unusual case in which a man committed suicide by using a shotgun shell, a shotgun barrel (separate from the rest of the gun), and a BB. Some confusion as to the cause and manner of death was present during the initial scene investigation. Examination at autopsy revealed the cause of death to be a shotgun wound of the chest and prompted further scene investigation. Therefore, this case serves as another example of the importance of cooperation between scene investigators and forensic pathologists when investigating a death. A review of suicidal firearm cases using unconventional means and/or firearms is presented.     

Transnational organized crime and gun violence. A case for firearm forensic intelligence sharing

A threat to the safety of citizens in any country, the criminal misuse of firearms presents a wider danger to a nation's security, peace, stability and development. Firearms and their related evidence know no borders. It is not uncommon to find the murder weapon from a shooting in one city ending up in another city, country, or continent. No country remains unaffected by firearm violence. This paper describes how transnational organized crime and gun violence are interrelated, and makes the case for the international sharing of firearm forensic intelligence through Interpol's IBIN Program as an integral component of an intelligence-led policing strategy to combat cross-border gun related crime. With such a strategy in place, internationally mobile criminals who use firearms to further their illicit activities can no longer escape detection.     

An Investigation into Whether or Not the Class and Individual Characteristics of Five Turkish Manufactured Pistols Change During Extensive Firing

Abstract:  In order to assess whether or not the class and individual characteristics of a firearm change over time, five different makes of Turkish self-loading pistol were tested and were each fired a large number of times. The class and individual characteristics were identified for each pistol and the first fired cartridge case was compared with the subsequent consecutive 250th fired cases for each pistol. It was found that there were slight changes in some of the individual and class characteristics; however, this was not statistically significant and did not affect the ability of the firearms examiner to match the first fired case to the last fired case for each firearm tested.     

Beyond CSI: Calibrating public beliefs about the reliability of forensic science through openness and transparency

What drives public beliefs about the credibility of a scientific field? This question is increasingly important, with recent discussion of a “reproducibility crisis” affecting many fields. Such discussions are vital in forensic science, a discipline that has experienced severe scrutiny from both the media and large oversight bodies. In this paper, we make three contributions to this discussion. First, we bring together and compare several studies in which laypeople were asked about the reliability of forensic science practices. This review suggests that forensic practices do not enjoy uniformly high reliability ratings from the public and these ratings are not calibrated with the scientific consensus. We then review three empirically-tested ways that other fields are dealing with their own crises, all centred around transparency and openness. Finally, we make recommendations for how forensic science can leverage transparency and openness to improve and maintain its long-term credibility. As part of these recommendations, we find that empirical research supports the Houston Forensic Science Center’s recent claims that it has improved its credibility through openness and transparency.     

The Mobility of Stolen Guns in Quebec

Research on crime guns has traditionally focused on the time-to-crime measure. This study shifts the focus to guns that entered the illegal firearm market through thefts. This subset of guns allows us to examine the same process and objective underlying the time-to-crime measure—that being the recovery process. Two new measures are proposed. The first, time-to-find, assesses the time span between a gun’s theft and seizure by police. The second, distance-to-recovery, introduces a spatial dimension to the crime gun repertoire by measuring the distance a firearm travels between its points of theft and seizure. Using a mix of national (Canada) and provincial (Quebec) data on crime guns, this study’s findings show that these two new measures are tapping into a unique phenomenon: whereas time-to-crime accounts for a gun’s complete lifecycle, time-to-find and distance-to-recovery reflect a gun’s criminal lifecycle. At the multivariate level, the most influential factor explaining both time-to-find and distance-to-recovery is the registration status of the gun. Non-registered crime guns took longer to find and traveled lengthier distances between the moments and points of theft and seizure. Our explanation for this is that non-registered guns may be stolen from sources that are more problematic to begin with and, thus, result in the gun’s transition toward a segment of the illegal market that is also more problematic and in demand than the pool of firearms represented by registered guns. This would embed the firearm more deeply into the illegal market, making it more difficult to retrieve and more likely to be dispersed across a wider geographical plane than guns which are registered to begin with.     

A simple and effective image-statistics-based approach to detecting recaptured images from LCD screens

It is now extremely easy to recapture high-resolution and high-quality images from LCD (Liquid Crystal Display) screens. Recaptured image detection is an important digital forensic problem, as image recapture is often involved in the creation of a fake image in an attempt to increase its visual plausibility. State-of-the-art image recapture forensic methods make use of strong prior knowledge about the recapturing process and are based on either the combination of a group of ad-hoc features or a specific and somehow complicated dictionary learning procedure. By contrast, we propose a conceptually simple yet effective method for recaptured image detection which is built upon simple image statistics and a very loose assumption about the recapturing process. The adopted features are pixel-wise correlation coefficients in image differential domains. Experimental results on two large databases of high-resolution, high-quality recaptured images and comparisons with existing methods demonstrate the forensic accuracy and the computational efficiency of the proposed method.     

Automatic forensic face recognition from digital images.

Digital image evidence is now widely available from criminal investigations and surveillance operations, often captured by security and surveillance CCTV. This has resulted in a growing demand from law enforcement agencies for automatic person-recognition based on image data. In forensic science, a fundamental requirement for such automatic face recognition is to evaluate the weight that can justifiably be attached to this recognition evidence in a scientific framework. This paper describes a pilot study carried out by the Forensic Science Service (UK) which explores the use of digital facial images in forensic investigation. For the purpose of the experiment a specific software package was chosen (Image Metrics Optasia). The paper does not describe the techniques used by the software to reach its decision of probabilistic matches to facial images, but accepts the output of the software as though it were a 'black box'. In this way, the paper lays a foundation for how face recognition systems can be compared in a forensic framework. The aim of the paper is to explore how reliably and under what conditions digital facial images can be presented in evidence.