Ram P. Krish

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In this study, the effects of using handheld devices on the performance of automatic signature verification systems are studied. The authors compare the discriminative power of global and local signature features between mobile devices and pen tablets, which are the prevalent acquisition device in the research literature. Individual feature discriminant(More)
The methodology currently practiced in latent print examination (known as ACE-V) yields only a decision as result, namely individualization, exclusion or inconclusive. From such a decision, it is not possible to express the strength of opinion of a forensic examiner quantitatively with a scientific basis to the criminal justice system. In this paper, we(More)
Minutia based matching scheme is the most widely accepted method for both automated as well as manual (forensic) fingerprint matching. The scenario of comparing a partial fingerprint minutia set against a full fingerprint minutia set is a challenging problem. In this work, we propose a method to register the orientation field of the partial fingerprint(More)
Comparing a latent fingerprint minutiae set against a tenprint fingerprint minutiae set using an automated fingerprint identification system is a challenging problem. This is mainly because latent fingerprints obtained from crime scenes are mostly partial fingerprints, and most automated systems expect approximately the same number of minutiae between query(More)
In this study, the authors present a hierarchical algorithm to register a partial fingerprint against a full fingerprint using only the orientation fields. In the first level, they shortlist possible locations for registering the partial fingerprint in the full fingerprint using a normalised correlation measure, taking various rotations into account. As a(More)
This work is focused on dynamic signature verification for state-of-the-art smart phones, including performance evaluation. The analysis was performed on database consisting of 25 users and 500 signatures in total acquired with Samsung Galaxy Note. The verification algorithm tested combines two approaches: feature based (using Mahalanobis distance) and(More)
The existing high resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy and focus on full-to-full/partial-to-full palmprint comparison. These algorithms would face problems when they are applied to forensic palmprint recognition where latent marks have much smaller area than full palmprints. Therefore,(More)
Recently, a novel matching strategy based on regional fusion for high resolution palmprint recognition arises for both forensic and civil applications, under the concept of different regional discriminability of three palm regions, i.e., interdigital, hypothenar and thenar. This matching strategy requires accurate automatic region segmentation techniques(More)
In this paper, we introduce an algorithm to generate a score from the matched templates derived by the forensic examiner at the ACE-V stage. Such a score can be viewed quantitatively as a measure of confidence of the forensic examiner for the given latent and impression prints. This quantitative measure can be used in statistics-based evidence evaluation(More)
Automated Fingerprint Identification Systems (AFIS) are commonly used by law enforcement agencies to narrow down the possible suspects from a criminal database. AFIS do not use all discriminatory features available in fingerprints but typically use only some types of features automatically extracted by a feature extraction algorithm. Latent fingerprints(More)
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