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Atomic Force Microscopy

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...

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Co-localizing Kelvin Probe Force Microscopy with Other Microscopies and Spectroscopies: Selected Applications in Corrosion Characterization of Alloys

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Forensic surface metrology: tool mark evidence.

Carol Gambino¹, Patrick McLaughlin, Loretta Kuo

¹Department of Sciences, John Jay College of Criminal Justice, City University of New York, New York, USA.

|June 29, 2011

Summary

This summary is machine-generated.

Forensic tool mark analysis can now be objectively corroborated. This study developed a new system using confocal microscopy, principal component analysis, and support vector machines to reduce subjectivity and provide confidence levels for evidence identification.

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Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

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Published on: April 29, 2014

Area of Science:

Forensic Science
Materials Science
Computer Science

Background:

Impression evidence analysis in forensics often relies on subjective comparisons, leading to courtroom scrutiny.
A lack of universally accepted systems for generating objective, numerical data to support visual comparisons in tool mark analysis exists.
This research addresses the need for objective methods in firearm and tool mark examination.

Purpose of the Study:

To develop a methodology for the objective evaluation and association of striated tool marks with their generating tools.
To introduce a system that generates numerical data to corroborate subjective visual comparisons in forensic tool mark analysis.
To establish confidence levels for tool mark identifications using conformal prediction theory.

Main Methods:

High-resolution white light confocal microscopy was used to collect 3D surface topographies of 58 primer shear marks from Glock 19 pistols.
Waviness profiles were extracted from the 3D surface data and processed using principal component analysis (PCA) for dimension reduction.
Support vector machines (SVM) were employed for profile-gun associations, with conformal prediction theory (CPT) used to establish confidence levels.

Main Results:

The combined PCA-SVM and CPT approach achieved an empirical error rate of 3.5% at the 95% confidence level.
Bootstrap-based computations indicated an estimated error rate of 0%, suggesting a low error rate for larger datasets.
The methodology successfully provided objective, quantifiable data to support the association of tool marks with specific firearms.

Conclusions:

The developed methodology offers an objective approach to tool mark analysis, reducing reliance on subjective comparisons.
Conformal prediction theory provides a robust framework for assigning confidence levels to algorithmic identifications in forensic science.
This system has practical implications for courtroom application, enhancing the reliability and admissibility of tool mark evidence.