UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at http://www.ucl.ac.uk/finance/research/post_award/post_award_contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
A Comparison of Thresholding Methods for Forensic Reconstruction Studies Using Fluorescent Powder Proxies for Trace Materials
Abstract
© 2018 The Authors Journal of Forensic Sciences published by Wiley Periodicals, Inc. on behalf of American Academy of Forensic Sciences Image segmentation is a fundamental precursor to quantitative image analysis. At present, no standardised methodology exists for segmenting images of fluorescent proxies for trace evidence. Experiments evaluated (i) whether manual segmentation is reproducible within and between examiners (with three participants repeatedly tracing three images) (ii) whether manually defining a threshold level offers accurate and reproducible results (with 20 examiners segmenting 10 images), and (iii) whether a global thresholding algorithm might perform with similar accuracy, while offering improved reproducibility and efficiency (16 algorithms tested). Statistically significant differences were seen between examiners’ traced outputs. Manually thresholding produced good accuracy on average (within ±1% of the expected values), but poor reproducibility (with multiple outliers). Three algorithms (Yen, MaxEntropy, and RenyiEntropy) offered similar accuracy, with improved reproducibility and efficiency. Together, these findings suggest that appropriate algorithms could perform thresholding tasks as part of a robust workflow for reconstruction studies employing fluorescent proxies for trace evidence.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers Show More
Author
Dept of Security and Crime Science
Author
Dept of Computer Science
Author
Dept of Geography
Author
Dept of Security and Crime Science
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by