سال انتشار: ۱۳۹۱

محل انتشار: بیستمین کنفرانس مهندسی برق ایران

تعداد صفحات: ۵

نویسنده(ها):

S. J. MousaviRad – University of Kurdistan
F. Akhlaghian Tab – University of Kurdistan
K. Mollazade – University of Kurdistan
K Nasri – University of Kurdistan

چکیده:

In this paper, an algorithm for classifying five different varieties of rice bulk samples is presented. Forty four features from co-occurrence matrix were extracted from bulksamples of rice. The Set of features contained redundant, noisy or even irrelevant information. So, features were evaluated bystandard sequential forward algorithm. Finally, ten features were selected as the superior ones. Support vector machine classifier was developed to classify rice varieties. The overall classification accuracy was achieved as 93.55%.