Add a logger assembly and split the main assembly in two : the UI and the parasitemia...

[master-thesis.git] / Parasitemia / ParasitemiaCore / Granulometry.fs

diff --git a/Parasitemia/ParasitemiaCore/Granulometry.fs b/Parasitemia/ParasitemiaCore/Granulometry.fs
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+++ b/Parasitemia/ParasitemiaCore/Granulometry.fs
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+module ParasitemiaCore.Granulometry
+
+open System
+open System.Drawing
+
+open Emgu.CV
+open Emgu.CV.Structure
+
+open Utils
+
+// 'range': a minimum and maximum radius.
+// 'scale': <= 1.0, to speed up the process.
+let findRadiusByClosing (img: Image<Gray, 'TDepth>) (range: int * int) (scale: float) : int =
+    use scaledImg = if scale = 1. then img else img.Resize(scale, CvEnum.Inter.Area)
+
+    let r1, r2 = range
+    let r1', r2' = roundInt (float r1 * scale), roundInt (float r2 * scale)
+
+    let patternSpectrum = Array.zeroCreate (r2' - r1')
+    let intensityImg = scaledImg.GetSum().Intensity
+
+    // 's' must be odd.
+    let octagon (s: int) : Matrix<byte> =
+        if s % 2 = 0 then failwith "s must be odd"
+        let m = new Matrix<byte>(Array2D.create s s 1uy)
+        let r = (float s) / (Math.Sqrt 2. + 2.) |> roundInt
+        for i in 0 .. r - 1 do
+            for j in 0 .. r - 1 do
+                if i + j < r
+                then
+                    m.[i, j] <- 0uy
+                    m.[s - i - 1, j] <- 0uy
+                    m.[i, s - j - 1] <- 0uy
+                    m.[s - i - 1, s - j - 1] <- 0uy
+        m
+
+    let mutable previous_n = Double.NaN
+    for r in r1' .. r2' do
+        let se = CvInvoke.GetStructuringElement(CvEnum.ElementShape.Ellipse, Size(2 * r, 2 * r), Point(-1, -1))
+        //let se = octagon (2 * r - 1)
+
+        use closed = scaledImg.MorphologyEx(CvEnum.MorphOp.Close, se, Point(-1, -1), 1, CvEnum.BorderType.Replicate, MCvScalar(0.0))
+
+        let n = closed.GetSum().Intensity
+
+        if not (Double.IsNaN previous_n)
+        then
+            patternSpectrum.[r - r1' - 1] <- abs (n - previous_n)
+        previous_n <- n
+
+    let max, _ = patternSpectrum |> Array.indexed |> Array.fold (fun (iMax, sMax) (i, s) -> if s > sMax then (i, s) else (iMax, sMax)) (0, Double.MinValue)
+
+    float (max + r1') / scale |> roundInt
+
+let findRadiusByAreaClosing (img: Image<Gray, float32>) (range: int * int) : int =
+    let r1, r2 = range
+
+    use imgCopy = img.Copy()
+
+    let mutable maxDiff = 0.f
+    let mutable max_r = r1
+
+    ImgTools.areaCloseFWithFun imgCopy [ for r in r1 .. r2 -> Math.PI * float r ** 2. |> roundInt, r ] (fun r diff ->
+        if r <> r1 && diff > maxDiff
+        then
+            maxDiff <- diff
+            max_r <- r - 1 )
+    max_r
+