Forensic Sciences has become an increasingly popular and useful field for organizations, and with current technological advances, new solutions for classifications, feature extraction, and pattern recognition are constantly being developed. Fusing knowledge bases in Forensic and Data Science is a continuous project Posh Informatics works on, based on Arian Osman’s research in fingerprints.

Currently, research in methodologies for extracting key features in fingerprints, including deltas and cores, is being performed using new mathematical theories, for which the preliminaries are showing promising results. By fusing these new mathematical theories with current technologies, it is quite possible a more robust implementation is in the making.

Not only is it imperative to come up with new and exciting ideas, it is equally as important to be able to communicate findings visually to allow users to easily identify and understand said findings. Fourier and Wavelet Space allows to determine certain patterns in frequencies within images and other signals. Having a deep mathematical foundation enables Posh Informatics to partake in this particular endeavor which will consequently result in publishable works in academic journals.

Items in queue for this particular research include the following:

• Sensitivity analysis
• Optimization
• Fusion with classification techniques
• Comparisons with features found in deep learning implementations

By having the mathematics and basic implementations in place, Posh Informatics is now able to perform the necessary analysis to verify whether or not this is a feasible solution to current problems existing within Forensic Sciences dealing with fingerprint images initially.