1822c75dc2221c0c7775f582c2c4700483ed086c
3 open System.Collections.Generic
13 d_fg
: Image<Gray, float32
> } // Distances to median_fg.
15 let kmedians (img
: Image<Gray, float32
>) (fgFactor
: float) : Result =
20 let min = ref [| 0.0
|]
21 let minLocation = ref <| [| Point() |]
22 let max = ref [| 0.0
|]
23 let maxLocation = ref <| [| Point() |]
24 img
.MinMax(min, max, minLocation, maxLocation)
26 let mutable median_bg = (!max).[0] - ((!max).[0] - (!min).[0]) / 4.0
27 let mutable median_fg = (!min).[0] + ((!max).[0] - (!min).[0]) / 4.0
28 use mutable d_bg = new Image<Gray, float32
>(img
.Size)
29 let mutable d_fg = new Image<Gray, float32
>(img
.Size)
30 let mutable fg = new Image<Gray, byte
>(img
.Size)
32 for i
in 1 .. nbIteration do
33 CvInvoke.Pow(img
- median_bg, 2.0, d_bg)
34 CvInvoke.Pow(img
- median_fg, 2.0, d_fg)
35 fg <- (d_fg * fgFactor
).Cmp(d_bg, CvEnum.CmpType.LessThan)
37 median_fg <- MathNet.Numerics.Statistics.Statistics.Median(seq
{
38 for i
in 0 .. h - 1 do
39 for j
in 0 .. w - 1 do
40 if fg.Data.[i
, j
, 0] > 0uy then yield img
.Data.[i
, j
, 0] |> float })
42 median_bg <- MathNet.Numerics.Statistics.Statistics.Median(seq
{
43 for i
in 0 .. h - 1 do
44 for j
in 0 .. w - 1 do
45 if fg.Data.[i
, j
, 0] = 0uy then yield img
.Data.[i
, j
, 0] |> float })
47 CvInvoke.Sqrt(d_fg, d_fg)
49 { fg = fg; median_bg = median_bg; median_fg = median_fg; d_fg = d_fg }