DocumentCode :
3488734
Title :
FREAK for Real Time Forensic Signature Verification
Author :
Malik, Muhammad Imran ; Ahmed, Shehab ; Liwicki, Marcus ; Dengel, Andreas
Author_Institution :
German Res. Center for Artificial Intell. (DFKI GmbH), Kaiserslautern, Germany
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
971
Lastpage :
975
Abstract :
This paper presents a novel signature verification system based on local features of signatures. The proposed system uses Fast Retina Key points (FREAK) which represent local features and are inspired by the human visual system, particularly the retina. To locate local points of interest in signatures, two local key point detectors, i.e., Features from Accelerated Segment Test (FAST) and Speeded-up Robust Features (SURF), have been used and their performance comparison in terms of Equal Error Rate (EER) and time is presented. The proposed system has been evaluated on publicly available dataset of forensic signature verification competition, 4NSigComp2010, which contains genuine, forged, and disguised signatures. The proposed system achieved an EER of 30%, which is considerably very low when compared against all the participants of the said competition. In addition to EER, the proposed system requires only 0.6 seconds on average to verify a 3000*1500 scanned signature. This shows that the proposed system has a potential and suitability for forensic signature verification as well as real time applications.
Keywords :
feature extraction; handwriting recognition; image representation; 4NSigComp2010; EER; FAST; FREAK; SURF; disguised signatures; equal error rate; fast retina key points; features from accelerated segment test; forensic signature verification competition; forged signatures; genuine signature; human visual system; local key point detectors; real time forensic signature verification system; signature local feature representation; speeded-up robust features; Conferences; Detectors; Feature extraction; Forensics; Forgery; Real-time systems; Retina; Forensic; Signature; Verification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
ISSN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2013.196
Filename :
6628761
Link To Document :
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