Detection　of　hard　exudates　from　fundus　images　is　crucial　since　hard　exudates　are　considered　to　be　one　of　the　most　prevalent　earliest　signs　of　retinopathy.　To　overcome　the　obstacles　in　retinal　exudates　identification,　such　as:　wide　variability　in　color,　illumination　uneven.　An　effective　approach　is　proposed.　After　preprocessing,　the　histogram　thresholding　is　used　to　recognize　the　background　and　object,　and　then　the　Fuzzy　C-Means(FCM)　technique　is　applied　to　assign　the　pixels　remain　unclassified　in　the　last　stage.　The　algorithm　performance　was　assessed　using　a　Standard　Diabetic　Retinopathy　Database　DIARETDB0.　The　proposed　algorithm　obtains　a　sensitivity　of　84.8%　and　a　predictive　value　of　87.5%　using　lesion-based　criterion,　The　experimental　results　show　that　the　proposed　approach　can　detect　hard　exudates　effectively.　©　2012　Springer-Verlag　GmbH.