سال انتشار: ۱۳۹۰

محل انتشار: هفتمین کنفرانس ماشین بینایی و پردازش تصویر

تعداد صفحات: ۵

نویسنده(ها):

Sadid Sahami – Department of Electrical EngineeringUrmia UniversityUrmia, Iran
Mehdi Chehel Amirani – Department of Electrical EngineeringUrmia UniversityUrmia, Iran

چکیده:

Spectral Correlation Function, (SCF), can providerich discriminative information for texture classification. Thispaper proposes the implementation of a new cyclostationaryanalyzer in texture classification. The results show StripSpectral Correlation Analyzer (SSCA), has bettercharacteristics in term of complexity and performance thanother frequency and time smoothed cyclostationary analysers.Our results introduce SSCA as a promising feature extractiontechnique for texture classification