X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FClassifier.fs;h=0d2137545334091fc551d17610ff5f6f69d49243;hp=f17c0b967695c5759c5443417ecc452e2d31a995;hb=53440e757b4a4ab2a81b0f6a5dd1a2002c0133ba;hpb=962440dfe579569ba7e3ebba6f878cb575d1fc02

diff --git a/Parasitemia/Parasitemia/Classifier.fs b/Parasitemia/Parasitemia/Classifier.fs
index f17c0b9..0d21375 100644
--- a/Parasitemia/Parasitemia/Classifier.fs
+++ b/Parasitemia/Parasitemia/Classifier.fs
@@ -93,7 +93,12 @@ let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img:
         // We reverse the list to get the lower score ellipses first.
         let ellipsesWithNeigbors = ellipses |> List.map (fun e -> e, neighbors e) |> List.rev
 
-        // 2) Remove ellipses with a high standard deviation (high contrast).
+
+        // 2) Remove ellipses touching the edges.
+        for e in ellipses do
+            if e.isOutside w_f h_f then e.Removed <- true
+
+        // 3) Remove ellipses with a high standard deviation (high contrast).
 
         // CvInvoke.Normalize(img, img, 0.0, 255.0, CvEnum.NormType.MinMax) // Not needed.
 
@@ -103,21 +108,20 @@ let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img:
                     yield float img.Data.[y, x, 0] })
 
         for e in ellipses do
-            let minX, minY, maxX, maxY = ellipseWindow e
-
-            let stdDeviation = MathNet.Numerics.Statistics.Statistics.StandardDeviation (seq {
-                for y in (if minY < 0 then 0 else minY) .. (if maxY >= h then h - 1 else maxY) do
-                    for x in (if minX < 0 then 0 else minX) .. (if maxX >= w then w - 1 else maxX) do
-                        if e.Contains (float x) (float y)
-                        then
-                            yield float img.Data.[y, x, 0] })
+            if not e.Removed
+            then
+                let shrinkedE = e.Scale 0.9
+                let minX, minY, maxX, maxY = ellipseWindow shrinkedE
 
-            if stdDeviation > globalStdDeviation * config.Parameters.standardDeviationMaxRatio then
-                e.Removed <- true
+                let stdDeviation = MathNet.Numerics.Statistics.Statistics.StandardDeviation (seq {
+                    for y in (if minY < 0 then 0 else minY) .. (if maxY >= h then h - 1 else maxY) do
+                        for x in (if minX < 0 then 0 else minX) .. (if maxX >= w then w - 1 else maxX) do
+                            if shrinkedE.Contains (float x) (float y)
+                            then
+                                yield float img.Data.[y, x, 0] })
 
-        // 3) Remove ellipses touching the edges.
-        for e in ellipses do
-            if e.isOutside w_f h_f then e.Removed <- true
+                if stdDeviation > globalStdDeviation * config.Parameters.standardDeviationMaxRatio then
+                    e.Removed <- true
 
         // 4) Remove ellipses with little area.
         let minArea = config.RBCMinArea