Title :
Signature Recognition using Cluster Based Global Features
Author :
Kekre, H.B. ; Bharadi, V.A.
Author_Institution :
NMIMS Univ., Mumbai
Abstract :
In this paper we discuss an off-line signature recognition system designed using clustering techniques. These cluster based features are mainly morphological feature, they include Walsh coefficients of pixel distributions, vector quantization based codeword histogram, grid & texture information features and geometric centers of a signature. In this paper we discuss the extraction and performance analysis of these features. We present the FAR, FRR achieved by the system using these features . We compare individual performance and overall system performance.
Keywords :
feature extraction; geometry; handwriting recognition; pattern clustering; vector quantisation; Walsh coefficients; cluster based features; clustering techniques; codeword histogram; grid information features; offline signature recognition system; texture information features; vector quantization; Communication system control; Communication system security; Control systems; Data security; Debugging; Frequency; RFID tags; Radiofrequency identification; Software systems; System testing;
Conference_Titel :
Advance Computing Conference, 2009. IACC 2009. IEEE International
Conference_Location :
Patiala
Print_ISBN :
978-1-4244-2927-1
Electronic_ISBN :
978-1-4244-2928-8
DOI :
10.1109/IADCC.2009.4809208
