ايناس البحباح, ليلي عبدالله اصميدة, طالب رمضان المحربي
English Authors
Ainas A. Albahbah, Laila Abdullah Esmeda , Taleb Almajrabi
Abstract
Nowadays, support vector machines (SVMs) has been used broadly to solve numerous
mind boggling issues in various fields because of its capacity to sum up and classify
perfectly. One of these fields is the medicinal image preparing for diagnosing purposes. In
this paper, tooth caries identification system is presented in light of SVMs that trained by
using practical swarm optimization (PSO). The proposed approach utilizes inter-pixel
autocorrelation as input features. Experimental results prove that the proposed approach can
detect tooth caries efficiently. Furthermore, it is clear that the classification accuracy is very
good. In addition, the proposed approach of tooth caries detection outperforms the
diagnosing process performed by a rule-based computer assisted program and a group of
dentists.