Date of Graduation

2015

Document Type

Thesis

Degree Type

MS

College

Eberly College of Arts and Sciences

Department

Forensic and Investigative Science

Committee Chair

Keith Morris

Committee Co-Chair

Eric Everts

Committee Member

Robert Johnson

Committee Member

Jacqueline Speir

Abstract

Latent fingerprints are highly common among evidence that is found at crime scenes. While fingerprint evidence can be very reliable, comparison and identification of a print is highly affected by the quality of the fingerprint image. Fingerprint experts ideally want to have an image with the best quality possible, in order to make an accurate identification and avoid missing pertinent details. This is a thesis presented on the use of digital image processing to merge multiple images of one fingerprint to obtain a final image with greater quality. The research was conducted using different latent fingerprint processing techniques that have been widely used in the forensic science community: ninhydrin, DFO, zinc chloride, cyanoacrylate, and fluorescent dye-stains. The latents were photographed after each technique was utilized. Images of the same print under different wavelengths and filters were merged to create a final image with ideally better contrast, quality, and friction ridge detail than were observed in the original images prior to merging. Quality was determined using three different scoring methods; NFIQ, Bandey scale, and AFIX Tracker. A print was considered to be improved if the merged score was better than the scores of the original images. There were 12.1 % of prints that were improved based on NFIQ scores, 2.8 % based on Bandey scores, and 15.0 % based on AFIX match scores. Image fusion for increasing quality of latent fingerprint images is a method that shows small benefits for the examiner when performing a comparison.

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