DocumentCode
2016892
Title
Wavelet Transform Based Global Features for Online Signature Recognition
Author
Afsar, F.A. ; Arif, M. ; Farrukh, U.
Author_Institution
Dept. of Comput. & Inf. Sci., Pakistan Inst. of Eng. & Appl. Sci., Islamabad
fYear
2005
fDate
24-25 Dec. 2005
Firstpage
1
Lastpage
6
Abstract
This paper presents an efficient algorithm for an online signature verification system that is based on the extraction of global features from the spatial coordinates obtained during the online acquisition of a signature using one dimensional wavelet transform. A k-NN classifier is used for classification purposes. Low error rates obtained for both random and skilled forgeries datasets illustrate the feasibility of the algorithm for an online signature verification system
Keywords
feature extraction; handwriting recognition; neural nets; pattern classification; wavelet transforms; global feature; neural net classifier; online signature recognition; wavelet transform; Authentication; Biometrics; Data mining; Error analysis; Feature extraction; Forgery; Handwriting recognition; Hidden Markov models; Spatial databases; Wavelet transforms; Biometrics; Signature Verification; Wavelet Transform; k-NN Classifier;
fLanguage
English
Publisher
ieee
Conference_Titel
9th International Multitopic Conference, IEEE INMIC 2005
Conference_Location
Karachi
Print_ISBN
0-7803-9429-1
Electronic_ISBN
0-7803-9430-5
Type
conf
DOI
10.1109/INMIC.2005.334431
Filename
4133446
Link To Document