toward automatic blood spatter analysis in crime scenes

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Toward Automatic Blood Spatter Analysis in Crime Scenes Gabriel Brostow, 13 June, 2 Shen, Brostow, Cipolla University of Cambridge

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Toward Automatic Blood Spatter Analysis in Crime Scenes. Gabriel Brostow, 13 June, 2006. Shen, Brostow, Cipolla University of Cambridge. Bloodstain Categories*. Passive Bloodstains Projected Bloodstains Low / medium / high velocity impact: caused by force applied to a blood source - PowerPoint PPT Presentation

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Page 1: Toward Automatic Blood Spatter Analysis in Crime Scenes

Toward Automatic Blood Spatter Analysis in Crime

Scenes

Gabriel Brostow, 13 June, 2006

Shen, Brostow, CipollaUniversity of Cambridge

Page 2: Toward Automatic Blood Spatter Analysis in Crime Scenes

Bloodstain Categories*

• Passive Bloodstains

• Projected Bloodstains– Low / medium / high velocity impact:

caused by force applied to a blood source

• Transfer/Contact Bloodstains

*International Association of Bloodstain Pattern Analysts

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Image by Kevin Maloney

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Point of Origin Localization

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String Method

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Support Software

From BackTrack software by A. L. Carter, 2001 version

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Automation Goals

1. Estimate impact angles for 1 spot

2. Estimate 2D origin of impact

3. Estimate 3D origin of impact

Page 9: Toward Automatic Blood Spatter Analysis in Crime Scenes

Automation Goals

1. Estimate impact angles for 1 spot

2. Estimate 2D origin of impact

3. Estimate 3D origin of impact

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Experimental Setup

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Results: Impact Angles

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Primary vs. Secondary Stains

Bevel & Gardner, 2001

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Filter for Outliers

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Automation Goals

1. Estimate impact angles for 1 spot

2. Estimate 2D origin of impact

3. Estimate 3D origin of impact

Page 16: Toward Automatic Blood Spatter Analysis in Crime Scenes

2D Multi-Spot Analysis

• Experiment– Blunt force impact– True origin:

• diameter 6cm• height 22cm

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Strings in the form of vectors

x

y

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Intersections

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Convolve with Gaussian

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Threshold on Distance

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Image rectification

• Generate synthetic view

• Homography:

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Image rectification

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Automation Goals

1. Estimate impact angles for 1 spot

2. Estimate 2D origin of impact

3. Estimate 3D origin of impact

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Height Estimation

• Triangulation– H = tan() * distance– True height 22cm,

estimated height 19cm

• Advanced– Unknowns– Speed, distance, air

resistance and gravity

Page 30: Toward Automatic Blood Spatter Analysis in Crime Scenes

Height Estimation

• Triangulation– H = tan() * distance– True height 22cm,

estimated height 19cm

• Model in future– Speed, distance, air

resistance and gravity

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Findings

• Demonstrated accuracy of 1-spot analysis

• 2D Origin of Impact Estimation

• Overhead crime-scene visualization

• Groundwork for 3D string method automation

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Future Work

• Real blood images

• 3D projectile trajectory modeling

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Related work

• Interpretation of Bloodstain Evidence at Crime Scenes – Eckert & James, 1998

• Bloodstain Pattern Analysis– Bevel & Gardner, 2001

• Blood Dynamics– Wonder, 2001

• The Directional Analysis of Bloodstain Patterns, Theory and Experimental Validation– A.L.Carter, 2001

Page 37: Toward Automatic Blood Spatter Analysis in Crime Scenes

Alternative bloodstain ellipse fitting

• Alternative ellipse fitting algorithm– Ellipse growth– Erosion, median filter

and dilation

Page 38: Toward Automatic Blood Spatter Analysis in Crime Scenes

Manual vs. Automatic

• Current pipeline:– On-site measurements– Physical strings

construction– Qualitative estimation

of origin

• Automatic pipeline:– Image processing– Strings in the form of

equations stored on computer

– Quantitative estimation of origin using error functions