X-Git-Url: http://git.euphorik.ch/?a=blobdiff_plain;f=Parasitemia%2FParasitemiaCore%2FImgTools%2FEdges.fs;h=63ec80a188cc2a0196f68126d66367cefca610df;hb=b87b35b922551f122228df1fd9c530bbb807935a;hp=b174ee9d060ed08ad4541b3e45112465cbe8a943;hpb=3f8b0d281b3058faf23dbd0363de440bd04c6574;p=master-thesis.git

diff --git a/Parasitemia/ParasitemiaCore/ImgTools/Edges.fs b/Parasitemia/ParasitemiaCore/ImgTools/Edges.fs
index b174ee9..63ec80a 100644
--- a/Parasitemia/ParasitemiaCore/ImgTools/Edges.fs
+++ b/Parasitemia/ParasitemiaCore/ImgTools/Edges.fs
@@ -11,19 +11,25 @@ open Const
 open Histogram
 open Otsu
 
+// Sensibilities of the hysteresis search.
+let sensibilityHigh = 0.1f
+let sensibilityLow = 0.0f
+
 /// <summary>
 /// Find edges of an image by using the Canny approach.
 /// The thresholds are automatically defined with otsu on gradient magnitudes.
 /// </summary>
 /// <param name="img"></param>
-let find (img: Image<Gray, float32>) : Matrix<byte> * Matrix<float32> * Matrix<float32> =
+let find (img : Image<Gray, float32>) : Matrix<byte> * Matrix<float32> * Matrix<float32> =
     let w = img.Width
     let h = img.Height
 
     use sobelKernel =
-        new Matrix<float32>(array2D [[ 1.0f; 0.0f; -1.0f ]
-                                     [ 2.0f; 0.0f; -2.0f ]
-                                     [ 1.0f; 0.0f; -1.0f ]])
+        new Matrix<float32>(
+            array2D [[ -1.0f; 0.0f; 1.0f ]
+                     [ -2.0f; 0.0f; 2.0f ]
+                     [ -1.0f; 0.0f; 1.0f ]]
+        )
 
     let xGradient = new Matrix<float32>(img.Size)
     let yGradient = new Matrix<float32>(img.Size)
@@ -32,11 +38,9 @@ let find (img: Image<Gray, float32>) : Matrix<byte> * Matrix<float32> * Matrix<f
 
     use magnitudes = new Matrix<float32>(xGradient.Size)
     use angles = new Matrix<float32>(xGradient.Size)
-    CvInvoke.CartToPolar(xGradient, yGradient, magnitudes, angles) // Compute the magnitudes and angles.
+    CvInvoke.CartToPolar(xGradient, yGradient, magnitudes, angles) // Compute the magnitudes and angles. The angles are between 0 and 2 * pi.
 
     let thresholdHigh, thresholdLow =
-        let sensibilityHigh = 0.1f
-        let sensibilityLow = 0.0f
         let threshold, _, _ = otsu (histogramMat magnitudes 300)
         threshold + (sensibilityHigh * threshold), threshold - (sensibilityLow * threshold)
 
@@ -49,46 +53,37 @@ let find (img: Image<Gray, float32>) : Matrix<byte> * Matrix<float32> * Matrix<f
     let xGradientData = xGradient.Data
     let yGradientData = yGradient.Data
 
-    for i in 0 .. h - 1 do
-        nmsData.[i, 0] <- 0uy
-        nmsData.[i, w - 1] <- 0uy
-
-    for j in 0 .. w - 1 do
-        nmsData.[0, j] <- 0uy
-        nmsData.[h - 1, j] <- 0uy
-
-    for i in 1 .. h - 2 do
-        for j in 1 .. w - 2 do
+    for i = 1 to h - 2 do
+        for j = 1 to w - 2 do
             let vx = xGradientData.[i, j]
             let vy = yGradientData.[i, j]
-            if vx <> 0.f || vy <> 0.f
-            then
+            if vx <> 0.f || vy <> 0.f then
                 let angle = anglesData.[i, j]
 
                 let vx', vy' = abs vx, abs vy
                 let ratio2 = if vx' > vy' then vy' / vx' else vx' / vy'
                 let ratio1 = 1.f - ratio2
 
-                let mNeigbors (sign: int) : float32 =
-                    if angle < PI / 4.f
-                    then ratio1 * magnitudesData.[i, j + sign] + ratio2 * magnitudesData.[i + sign, j + sign]
-                    elif angle < PI / 2.f
-                    then ratio2 * magnitudesData.[i + sign, j + sign] + ratio1 * magnitudesData.[i + sign, j]
-                    elif angle < 3.f * PI / 4.f
-                    then ratio1 * magnitudesData.[i + sign, j] + ratio2 * magnitudesData.[i + sign, j - sign]
-                    elif angle < PI
-                    then ratio2 * magnitudesData.[i + sign, j - sign] + ratio1 * magnitudesData.[i, j - sign]
-                    elif angle < 5.f * PI / 4.f
-                    then ratio1 * magnitudesData.[i, j - sign] + ratio2 * magnitudesData.[i - sign, j - sign]
-                    elif angle < 3.f * PI / 2.f
-                    then ratio2 * magnitudesData.[i - sign, j - sign] + ratio1 * magnitudesData.[i - sign, j]
-                    elif angle < 7.f * PI / 4.f
-                    then ratio1 * magnitudesData.[i - sign, j] + ratio2 * magnitudesData.[i - sign, j + sign]
-                    else ratio2 * magnitudesData.[i - sign, j + sign] + ratio1 * magnitudesData.[i, j + sign]
+                let mNeigbors (sign : int) : float32 =
+                    if angle < PI / 4.f then
+                        ratio1 * magnitudesData.[i, j + sign] + ratio2 * magnitudesData.[i + sign, j + sign]
+                    elif angle < PI / 2.f then
+                        ratio2 * magnitudesData.[i + sign, j + sign] + ratio1 * magnitudesData.[i + sign, j]
+                    elif angle < 3.f * PI / 4.f then
+                        ratio1 * magnitudesData.[i + sign, j] + ratio2 * magnitudesData.[i + sign, j - sign]
+                    elif angle < PI then
+                        ratio2 * magnitudesData.[i + sign, j - sign] + ratio1 * magnitudesData.[i, j - sign]
+                    elif angle < 5.f * PI / 4.f then
+                        ratio1 * magnitudesData.[i, j - sign] + ratio2 * magnitudesData.[i - sign, j - sign]
+                    elif angle < 3.f * PI / 2.f then
+                        ratio2 * magnitudesData.[i - sign, j - sign] + ratio1 * magnitudesData.[i - sign, j]
+                    elif angle < 7.f * PI / 4.f then
+                        ratio1 * magnitudesData.[i - sign, j] + ratio2 * magnitudesData.[i - sign, j + sign]
+                    else
+                        ratio2 * magnitudesData.[i - sign, j + sign] + ratio1 * magnitudesData.[i, j + sign]
 
                 let m = magnitudesData.[i, j]
-                if m >= thresholdLow && m > mNeigbors 1 && m > mNeigbors -1
-                then
+                if m >= thresholdLow && m > mNeigbors 1 && m > mNeigbors -1 then
                     nmsData.[i, j] <- 1uy
 
     // suppressMConnections nms // It's not helpful for the rest of the process (ellipse detection).
@@ -98,23 +93,20 @@ let find (img: Image<Gray, float32>) : Matrix<byte> * Matrix<float32> * Matrix<f
 
     // Hysteresis thresholding.
     let toVisit = Stack<Point>()
-    for i in 0 .. h - 1 do
-        for j in 0 .. w - 1 do
-            if nmsData.[i, j] = 1uy && magnitudesData.[i, j] >= thresholdHigh
-            then
+    for i = 0 to h - 1 do
+        for j = 0 to w - 1 do
+            if nmsData.[i, j] = 1uy && magnitudesData.[i, j] >= thresholdHigh then
                 nmsData.[i, j] <- 0uy
                 toVisit.Push(Point(j, i))
                 while toVisit.Count > 0 do
                     let p = toVisit.Pop()
                     edgesData.[p.Y, p.X] <- 1uy
-                    for i' in -1 .. 1  do
-                        for j' in -1 .. 1 do
-                            if i' <> 0 || j' <> 0
-                            then
+                    for i' = -1 to 1  do
+                        for j' = -1 to 1 do
+                            if i' <> 0 || j' <> 0 then
                                 let ni = p.Y + i'
                                 let nj = p.X + j'
-                                if ni >= 0 && ni < h && nj >= 0 && nj < w && nmsData.[ni, nj] = 1uy
-                                then
+                                if ni >= 0 && ni < h && nj >= 0 && nj < w && nmsData.[ni, nj] = 1uy then
                                     nmsData.[ni, nj] <- 0uy
                                     toVisit.Push(Point(nj, ni))