Density Optimization for Digital Dental Imaging System Using Fuzzy Reasoning and C-Means Clustering

Abstract

The digital dental imaging system (DDIS) has been developed and spread widely in recent years. The images of DDIS, however, aren't always so good, because of insufficient density distribution. Therefore, it seems that DDIS requires density optimization in an appropriate way. The authors applied the fuzzy reasoning and fuzzy c-means clustering algorithm for this purpose. According to our method, density distribution of most DDIS images could be improved better than the conventional histogram equalization method.