DocumentCode :
3189485
Title :
Identification of authors of documents based on offline signature recognition
Author :
Marusic, Tonco ; Marusic, Zeljko ; Seremet, Zeljko
Author_Institution :
Fac. of Sci. & Educ., Univ. of Mostar, Mostar, Bosnia-Herzegovina
fYear :
2015
fDate :
25-29 May 2015
Firstpage :
1144
Lastpage :
1149
Abstract :
Handwritten signature is used in various applications on daily basis. Whether one signs a contract, work documents, petition, or wants to approve a check payment, one will use personal signature to do all those things. In this paper we use this daily based biometric characteristic for identification and classification of students´ papers and various exam documents used at University of Mostar. In this paper we used OpenCV library as an image processing tool for feature extraction. As regards to classification method, we used Support Vector Machine.
Keywords :
feature extraction; handwriting recognition; image classification; support vector machines; OpenCV library; author document identification; biometric characteristic; exam document classification; exam document identification; feature extraction; handwritten signature; image processing tool; offline signature recognition; personal signature; student paper classification; student paper identification; support vector machine; Databases; Feature extraction; Gravity; Skeleton; Support vector machines; Testing; Wiener filters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2015 38th International Convention on
Conference_Location :
Opatija
Type :
conf
DOI :
10.1109/MIPRO.2015.7160447
Filename :
7160447
Link To Document :
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