Gold　immunochromatographic　strip　(GICS)　quantitative　detective　can　provide　more　information　than　the　qualitative　or　semiquantitative　testing.　In　this　paper,　a　fast　color　image　segmentation　method　is　presented　to　develop　the　quantitative　detective　of　GICS.　The　image　of　GICS　was　acquired　by　Charge-coupled　Device　(CCD)　image　sensor,　and　segmented　by　fuzzy　c-means　(FCM)　clustering　algorithm　based　on　color　histogram　in　HSV　color　space.　Maximin-distance　algorithm　was　adopted　to　get　the　initial　positions　of　centroids　and　cluster　number　to　overcome　the　shortcoming　that　the　FCM　algorithm　may　produce　local　optimal　results.　For　the　segmented　target　image,　a　special　characteristic　parameter　was　constructed　and　calculated　in　HSV　color　space　to　achieve　the　quantitative　interpretation　of　the　GICS.