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"Bullets Identification."
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Ballistics
\"A shooting has occurred. Investigators have not yet found evidence. Then they look in a storm drain and find shell casings. They put the casings in a paper bag and send them to the lab to be analyzed. Find out about the techniques and tools ballistics experts use to help bring even the toughest cases to a close\"-- Provided by publisher.
Book
Forensic ballistics in court
Forensic Ballistics in Court: Interpretation and Presentation of Firearms Evidence is an accessible introduction to firearms and ballistics evidence and how this is analysed and presented as evidence in a court of law.
The book approaches the subject in terms of the realities of case work, opening with a clear and illustrated explanation of the correct nomenclature for various weapon types and their parts. Ammunition is also extensively covered, again with annotated illustrations. Basic external and terminal ballistics, wounding capabilities are likewise covered to give an overview of the subject. A key aspect of the book covers the theory and philosophy behind striation matches and the associated statistics, how positive matches should be peer reviewed and the importance accreditation has on this subject.
Gunshot residue formation and identification and the various methods used in its analysis are reviewed in depth. This includes a critical examination of the pros and cons of each type of examination and the evidential weight which can be applied to each method.
* Accessible and reader-friendly introduction to firearms and ballistics.
* Clarifies the limitations of firearms evidence.
* Extensive use of global case-studies throughout.
* Focus on the interpretation and assessment of the weight of firearms/ballistics evidence presented at court.
* Covers the importance of witness and accused statements and their interpretation in relation to the investigation under review.
* Includes coverage of gunshot residue collection, examination and interpretation and the potential for contamination of GSR samples.
* Includes numerous real life case studies that the author has dealt with over the past 45 years.
* Takes an applied approach to the subject.
eBook
Ballistic Imaging
Ballistic Imaging assesses the state of computer-based imaging technology in forensic firearms identification. The book evaluates the current law enforcement database of images of crime-related cartridge cases and bullets and recommends ways to improve the usefulness of the technology for suggesting leads in criminal investigations. It also advises against the construction of a national reference database that would include images from test-fires of every newly manufactured or imported firearm in the United States. The book also suggests further research on an alternate method for generating an investigative lead to the location where a gun was first sold: \"microstamping,\" the direct imprinting of unique identifiers on firearm parts or ammunition.
eBook
Forensic Analysis
Since the 1960s, testimony by representatives of the Federal Bureau of Investigation
in thousands of criminal cases has relied on evidence from Compositional Analysis of
Bullet Lead (CABL), a forensic technique that compares the elemental composition of
bullets found at a crime scene to the elemental composition of bullets found in a
suspect's possession. Different from ballistics techniques that compare striations on
the barrel of a gun to those on a recovered bullet, CABL is used when no gun is
recovered or when bullets are too small or mangled to observe striations. Forensic
Analysis: Weighing Bullet Lead Evidence assesses the scientific validity of CABL, finding
that the FBI should use a different statistical analysis for the technique and that,
given variations in bullet manufacturing processes, expert witnesses should make
clear the very limited conclusions that CABL results can support. The report also recommends
that the FBI take additional measures to ensure the validity of CABL
results, which include improving documentation, publishing details, and improving
on training and oversight.
eBook
A correlation based bullet identification method using empirical mode decomposition
•Proposing an accurate bullet identification method.•Proposing a method to compare non stationary striations based on EMD.•Proposing a method to estimate rotation of images.•Proposing use of average profile and level of signal decomposing.•Comparing the method with related works to shows its better performance.
The striations on bullet surface are 3D micro structures formed when a bullet is forcing its way out of barrel. Each barrel leaves individual striation patterns on bullets. Hence, the striation information of bullets is helpful for firearm identification. Common automatic identification methods process these images using linear time invariant (LTI) filters based on correlation. These methods do not consider the sensitivity of correlation based comparisons to nonlinear baseline drifts. The striations are undeniably random unique micro structures caused by random non-model-based imperfections in the tools used in rifling process, therefore any characteristic profile that is extracted from a bullet image is statistically non-stationary. Due to limitations of LTI filters, using them in smoothing bullet images and profiles may cause information loss and impact the process of identification. To address these problems, in this article, we consider bullet images as nonlinear non-stationary processes and propose a novel method which uses ensemble empirical mode decomposition (EEMD) as a preprocessing algorithm for smoothing and feature extraction. The features extracted by EEMD algorithm not only contain less noise, but also have no nonlinear baseline drifts. These improvements help the correlation based comparison methods to perform more robustly and efficiently. The experiments showed that our proposed method attained better results compared with two common methods in the field of automatic bullet identification.
Journal Article
Development of an objective method for the comparison of fired projectiles using an air pistol as a template
•A single weapon does not necessarily leave identical marks on projectiles.•A mathematical methodology was developed to pre-process the striation marks for comparison.•Striation marks on projectiles can be objectively measured for identification.
The ability to objectify ballistic evidence is a challenge faced by firearms examiners around the world. A number of researchers are trying to improve bullet-identification systems to address deficiencies detailed within the National Academy of Science report (2009). More recently focus has turned to making use of more sophisticated imaging modalities to view entire regions of the projectile and the development of automated systems for the comparison of the topographical surfaces recorded. Projectiles from a newly bought air pistol with 0.177 calibre pellets (unjacketed), fired series of 609 pellets were examined using an optical microscope. A mathematical methodology was developed to pre-process the resultant topographical maps generating point data for comparison, analysed using the principal component analysis (PCA). In most cases limited to reasonable success was achieved. The objective method still requires an operator to identify the Land Engraved Areas to be scanned, however the mathematical alignments were objectively achieved. The PCA results illustrated that the striation marks were neither exclusive nor specific to the LEA regions but rather crossed over regions. This study also proves that a single weapon does not necessarily leave identical marks of projectiles on its surface.
Journal Article
Forensic Evidence Field Guide
Forensic Evidence Field Guide: A Collection of Best Practices highlights the essentials needed to collect evidence at a crime scene.The unique spiral bound design is perfect for use in the day-to-day tasks involved in collecting evidence in the field.
eBook
Algorithm for Automatic 3-D Scanned Bullet Identification Based on the Principle of Human Vision
Bullet identification is a complicated work which demands high accuracy rate. In this paper, we try to find a reliable and fast automatic bullet identification algorithm using image processing technology. The key and most difficult step is to find an image feature which can describe the unique striation pattern on the bullet. When we do bullet identification by human-eye, we try to best match the striations of the bullets. It’s mainly according to the order of the striations and the distance between them. Based on this principle, a new algorithm for automatic bullet identification is proposed. Using the bullet’s visual graphic set which is offered by the Three-Dimensional Laser Color Scanner (3DLCS), we firstly do pre-processing to the bullet unwrapped image, such as image enhancement, edge detecting, binarization, thinning and denoising, to obtain an image with clear striations and low noises. Then we find an effective image feature based on the principle of human vision: the bullet feature vectors (BFVs). According to actual needs, we give a reasonable definition for vector distance (VD) between vectors of different dimensions, and take VD of BFVs as a measurement for bullet similarity. Experimental results prove that our algorithm can correctly find the bullets with high trace similarity and do bullet identification successfully.
Journal Article
