An Algorithm of Cigarette Authentication Based on Morphological Processing and SVM

Author

Yuanyuan Zhang ; Guangmin Sun ; Qian Ren ; Dequn Zhao

Author_Institution

Dept. of Electron. Eng., Beijing Univ. of Technol., Beijing, China

Volume

2

fYear

2012

fDate

28-29 Oct. 2012

Firstpage

190

Lastpage

193

Abstract

It is obvious that the characters are illegible and the printing is rough on the package of fake cigarettes compared to genuine ones. According to the differences of comparison, we can make a two-class classifier to conduct cigarette authentication. in this paper, we firstly both extract morphological features of fake and genuine cigarettes and then use them as training sample sets to train a two-class SVM classifier. This algorithm has been tested on five brands of cigarettes and it gives results with more than 95% accuracy.

Keywords

feature extraction; image classification; learning (artificial intelligence); support vector machines; tobacco products; cigarette authentication; morphological feature extraction; morphological processing; support vector machines; two-class SVM classifier; Accuracy; Authentication; Feature extraction; Kernel; Morphology; Support vector machines; Training; LIBSVM; Morphological processing; OpenCV; Support Vector Machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-2646-9

Type

conf

DOI

10.1109/ISCID.2012.199

Filename

6405962