When suspects of crimes are caught by the police, their facial images and fingerprints are recorded and added to the extensive databases they have. If on a crime scene fingermarks are found they are compared to the databases using advanced fingerprint matching algorithms and in this way it is possible to obtain a short list of suspects quickly. However, when the fingerprints are recorded at the police office, sometimes traces of other fingerprints are left on the glass plate of the fingerprint sensor. Also, sometimes, the calibration of the sensor is not performed correctly and a "negative" of the previous fingerprint is stored. The left traces are mixed with the new fingerprint forming a ghost fingerprint pattern, often called "ghost" for short. In the databases of the police such ghosts are present, but it is not known how many and how serious the effect is. Of course they interfere with the proper recognition of fingerprints, sometimes giving a wrong match, sometimes causing a failure to match a fingerprint. This presentation gives an overview of the various approaches we attempted to detect these ghost fingerprints and estimate their impact on the matching process.
|Title of host publication||EAB Webinars|
|Publication status||Published - Nov 2020|