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[master-thesis.git] / Parasitemia / Parasitemia / KMedians.fs

diff --git a/Parasitemia/Parasitemia/KMedians.fs b/Parasitemia/Parasitemia/KMedians.fs
index 09d6c8f..82e09cb 100644 (file)
--- a/Parasitemia/Parasitemia/KMedians.fs
+++ b/Parasitemia/Parasitemia/KMedians.fs
@@ -22,28 +22,28 @@ let kmedians (img: Image<Gray, float32>) (fgFactor: float) : Result =
     let max = ref [| 0.0 |]
     let maxLocation = ref <| [| Point() |]
     img.MinMax(min, max, minLocation, maxLocation)
-    
+
     let mutable median_bg = (!max).[0] - ((!max).[0] - (!min).[0]) / 4.0
     let mutable median_fg = (!min).[0] + ((!max).[0] - (!min).[0]) / 4.0
     let mutable d_bg = new Image<Gray, float32>(img.Size)
     let mutable d_fg = new Image<Gray, float32>(img.Size)
     let mutable fg = new Image<Gray, byte>(img.Size)
-    
+
     for i in 1..nbIteration do
         CvInvoke.Pow(img - median_bg, 2.0, d_bg)
         CvInvoke.Pow(img - median_fg, 2.0, d_fg)
         fg <- (d_fg * fgFactor).Cmp(d_bg, CvEnum.CmpType.LessThan)
-        
+
         median_fg <- MathNet.Numerics.Statistics.Statistics.Median(seq {
             for i in 0 .. h - 1 do
                 for j in 0 .. w - 1 do
                     if fg.Data.[i, j, 0] > 0uy then yield img.Data.[i, j, 0] |> float })
-         
+
         median_bg <- MathNet.Numerics.Statistics.Statistics.Median(seq {
             for i in 0 .. h - 1 do
                 for j in 0 .. w - 1 do
                     if fg.Data.[i, j, 0] = 0uy then yield img.Data.[i, j, 0] |> float })
-                        
+
     CvInvoke.Sqrt(d_fg, d_fg)
 
     { fg = fg; median_bg = median_bg; median_fg = median_fg; d_fg = d_fg }