2012 MRes projects
- Twitter and Crime: The spatio-temporal link between social-media and criminal activity
- To what extent do water treatment processes affect the concentration of peroxide explosives in river water?
- Dual-band Frequency Reconfigurable Antennas
- Incorporating Nanostructures to Enhance the Performance of Semiconducting Metal
- A relevance study determining the use of GSR upon clothing and shoes as an item of evidence
- Automating the conceptual analysis of large-scale text-based subjective data sets
- Assessing the potential of e-noses for illicit drug detection in future drug-trafficking interdiction strategies
- Judgement in UK fingermark recovery: room for development?
- Modelling the allocation of crowd control resources
- Comparative study of the different feature extraction algorithms used for fingerprint identification
- Domain Adaptation of Statistical Classifiers for Security-related Bug Reports
- The detection of clandestine methamphetamine laboratories using semiconducting metal oxide gas sensors
- The evaluation of geochemical analysis methods for forensic provenance and interpretation
- Confirmation bias: A Study of biasability within Forensic anthropological visual assessments on skeletal remains
- Statistical change point detection of internet traffic
- Trace evidence dynamics: assessing the transfer and persistence of microbial diatom evidence in forensic investigation
- Data Communication for Underwater Sensor Networks
- Automated Cargo Inspection: Exploring the use of Machine Vision in X-ray Transmission Imaging
- Network Externalities and Migration: An Agent-Based Model Distinguishing Documented and Undocumented Flows
Comparative study of the different feature extraction algorithms used for fingerprint identification
21 March 2013
The research work is particularly aimed at quantitative comparison of the various feature extraction techniques that could be used individually or in combination for fingerprint identification. To test the robustness of the feature extraction algorithms, I intend to use a dataset having fingerprints of varying quality and orientation. The different feature extraction techniques that I intend to compare include, fingerprint minutiae extraction algorithm, principal component analysis and 2D Log Gabor filters. The quality of the fingerprint image greatly influences the performance of the feature extraction algorithms. This research work aims at combining the best image processing techniques, feature extraction procedures and pattern matching algorithms that have been used in face recognition and other forensic investigation genres, to mark out a set of feature extraction techniques that could facilitate near accurate identification of low quality, crime scene fingerprints. The research work though concentrates on working with latent fingerprints, is extendable to impressed as also plastic/ visible fingerprints. This work would sure help revolutionize the entire process of fingerprint identification. The 2004 Brandon Mayfield case highlights the need for a better, more robust, statistically more accurate and hence more reliable system for pattern recognition in the forensic domain. This research work aims at addressing this particular need.