ファジィ推論とc-meansクラスタリングによる歯科用デジタル画像診断システムの濃度の最適化(一般講演-画像2-)

抄録

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.