X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FKMedians.fs;fp=Parasitemia%2FParasitemia%2FKMedians.fs;h=0000000000000000000000000000000000000000;hp=d0056510551fdd63b0367f33958f8118d21035b6;hb=4bfa3cbdc6145e6944f02e24829ab2ef3a851ac1;hpb=48ecdfc43001c444eff6ad442986049384674af2

diff --git a/Parasitemia/Parasitemia/KMedians.fs b/Parasitemia/Parasitemia/KMedians.fs
deleted file mode 100644
index d005651..0000000
--- a/Parasitemia/Parasitemia/KMedians.fs
+++ /dev/null
@@ -1,54 +0,0 @@
-module KMedians
-
-open System.Collections.Generic
-open System.Drawing
-
-open Emgu.CV
-open Emgu.CV.Structure
-
-type Result = {
-    fg: Image<Gray, byte>
-    median_bg: float
-    median_fg: float
-    d_fg: Image<Gray, float32> } // Euclidean distances of the foreground to median_fg.
-
-let kmedians (img: Image<Gray, float32>) : Result =
-    let nbIteration = 4
-    let w = img.Width
-    let h = img.Height
-
-    let min = ref [| 0.0 |]
-    let minLocation = ref <| [| Point() |]
-    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
-    use 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
-        d_bg <- img.AbsDiff(Gray(median_bg))
-        d_fg <- img.AbsDiff(Gray(median_fg))
-
-        CvInvoke.Compare(d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
-
-        let bg_values = List<float>()
-        let fg_values = List<float>()
-
-        for i in 0 .. h - 1 do
-            for j in 0 .. w - 1 do
-                if fg.Data.[i, j, 0] > 0uy
-                then fg_values.Add(float img.Data.[i, j, 0])
-                else bg_values.Add(float img.Data.[i, j, 0])
-
-        median_bg <- MathNet.Numerics.Statistics.Statistics.Median(bg_values)
-        median_fg <- MathNet.Numerics.Statistics.Statistics.Median(fg_values)
-
-    { fg = fg; median_bg = median_bg; median_fg = median_fg; d_fg = d_fg }
-
-
-
-