چکیده مقاله
In recent years significant efforts have been made to provide an automated classification system for the classification of ancient coins The process of classifying ancient coins is faced with numerous problems that algorithms like SIFT are not able to solve all of them The purpose of this paper is toprovide a method for classifying ancient coins using a combination of statistical features The statistical features fusion extracted from BDPCA, DWT and DCT transforms by producing suitable feature vectorwith smaller size improves the overall performance of the system To increase the accuracy rate of theproposed system the signs engraved on the coins that have not been considered in previous work, are addressed The performed experiments present 88 17% of accuracy rate in the recognition process with applying this method on 7 databases of the Sassanin coins’ images
کلیدواژهها
نویسندگان
Seyyedeh-Sahar Parsa
Islamic Azad University saveh branch
Maryam Rastgarpour
Islamic Azad University saveh branch
شیوه ارجاع
Parsa, Seyyedeh-Sahar and Rastgarpour, Maryam,1394,Classification of Sassanin Coin Images Using Statistical Features Fusion,International Conference on New Research Findings in Electrical Engineering and Computer Science,Tehran
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