Title :
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
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;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
DOI :
10.1109/ISCID.2012.199
