Automated comparisons of bullet striations based on 3D topography

Kinder, Jan De; Bonfanti, M.

doi:10.1016/s0379-0738(98)00212-6

Cited by 48 publications

(27 citation statements)

References 2 publications

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“…1(b). Generally, automatic identification systems for bullets create a feature profile by averaging multiple cross section profiles [5,7,10,11] instead of using a single section, thus attenuating the effects of random errors. Optimal feature profiles and higher bullet identification accuracy should also be achieved if those areas that do not contain valid striation information are excluded through certain processing before the averaging is calculated.…”

Section: Methodsmentioning

confidence: 99%

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Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria

Chu

Thompson

Song

et al. 2013

Forensic Science International

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Section: Methodsmentioning

confidence: 99%

“…[ [5][6][7][8][9][10][11] and commercial product manufacturers [12-16] refer to optical photographic images as 2D where the value at each pixel point represents the intensity of reflected light at the point, and topographic images as 3D where the value at each pixel point represents its topographic height at the point.…”

Section: Introductionmentioning

confidence: 99%

Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria

Chu

Thompson

Song

et al. 2013

Forensic Science International

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“…More recently, approaches based on 3D digital representations of evidence surface topography have started to appear, both in research, Kinder and Bonfanti [1], Fernado [2], and Bachrach [3] and as industrial products, such as BulletTRAX-3D system by Forensic Tech. Inc. [4].…”

Section: Introductionmentioning

confidence: 99%

Automated bullet-identification system based on surface topography techniques

Xie¹,

Xiao²,

Blunt³

et al. 2009

Wear

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a b s t r a c tEvery firearm has individual characteristics that are as unique to it as fingerprints are to human beings. When a firearm is fired, it transfers these characteristics -in the form of microscopic scratches and dentsto the fired bullets and cartridge casings. The rifling of the barrel of the firearm marks the bullets travelling through it, and the firearm's breech mechanism marks the ammunition's cartridge casing. Characterising these marks is the critical element in identifying firearms.Traditionally the comparison of ballistic evidence has been a tedious and time-consuming process requiring highly skilled examiners. In the past decade, engineers have created automated ballistics identification systems that meld traditional comparison microscopes with digital cameras, computers, huge databases, and image analysis techniques. This kind of system can help investigators to link crimes by automatically finding similarities among images of bullet but suffering significant drawbacks and minimal matching.More recently, approaches based on 3D digital representations of evidence surface topography have started to appear, both in research and industrial products. Potentially the introduction of 3D surface topography measurement can overcome the limitations of digital imaging systems by making the bullet surface measurement reproducible and reliable. A 3D quantitative approach for bullet identification is proposed in this paper. In this system the surface topography of the whole bullet can be acquired for analysis and identification. Primary researches have been done by applying advanced surface topography techniques for bullet marks' characteristics extraction. A variety of 2D and 3D visualization graphics have also been provided to help firearm examiners to make final decisions.

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“…Although there are some researches on 3D surfaces of bullets and tool marks [1][2][3], they had not led to shape comparisons by using 3D surface data directly. In the field of Japanese archaeology, Masuda et al [4] have analyzed shape difference of ancient bronze mirrors with a method of computer vision.…”

Section: Introductionmentioning

confidence: 99%