- let neighbors (e: Ellipse) : (EllipseFlaggedKd * PointD * PointD) list =
- tree.Search (searchRegion e)
- // We only keep the ellipses touching 'e'.
- |> List.choose (fun otherE ->
- match EEOver.EEOverlapArea e otherE with
- | Some (area, px, py) when area > 0.0 && px.Length >= 2 && py.Length >= 2 ->
- Some (otherE, PointD(px.[0], py.[0]), PointD(px.[1], py.[1]))
- | _ ->
- None )
-
- let ellipsesWithNeigbors = ellipses |> List.choose (fun e -> if e.Removed then None else Some (e, neighbors e))
-
- // 2) Remove ellipses with a lower percentage of foreground. (taken from the lower score to the highest).
- (*for e, neighbors in List.rev ellipsesWithNeigbors do
+ let neighbors (e: EllipseFlaggedKd) : (EllipseFlaggedKd * PointD * PointD) list =
+ if not e.Removed
+ then
+ tree.Search (searchRegion e)
+ // We only keep the ellipses touching 'e'.
+ |> List.choose (fun otherE ->
+ match EEOver.EEOverlapArea e otherE with
+ | Some (_, px, _) when px.Length > 2 ->
+ otherE.Removed <- true
+ None
+ | Some (area, px, py) when area > 0.0 && px.Length = 2 ->
+ Some (otherE, PointD(px.[0], py.[0]), PointD(px.[1], py.[1]))
+ | _ ->
+ None )
+ else
+ []
+
+ // 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).
+
+ // 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 float img.Data.[y, x, 0] })
+
+ for e in ellipses do