X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FClassifier.fs;h=0d2137545334091fc551d17610ff5f6f69d49243;hp=7f11e13661fc2cb9fa667953597be51b40c0faf2;hb=53440e757b4a4ab2a81b0f6a5dd1a2002c0133ba;hpb=bef2e9f0bf1bba21d4c988fdf654c2dc303ec34a diff --git a/Parasitemia/Parasitemia/Classifier.fs b/Parasitemia/Parasitemia/Classifier.fs index 7f11e13..0d21375 100644 --- a/Parasitemia/Parasitemia/Classifier.fs +++ b/Parasitemia/Parasitemia/Classifier.fs @@ -21,7 +21,7 @@ type private EllipseFlaggedKd (e: Ellipse) = member this.Y = this.Cy -let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img: Image) (config: Config.Config) : Cell list = +let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img: Image) (config: Config.Config) : Cell list = if ellipses.IsEmpty then [] @@ -93,31 +93,35 @@ 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. let globalStdDeviation = MathNet.Numerics.Statistics.Statistics.StandardDeviation(seq { for y in 0 .. h - 1 do for x in 0 .. w - 1 do - yield img.Data.[y, x, 0] |> float }) + 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