open Emgu.CV
open Emgu.CV.Structure
-type Result = {
- fg: Image<Gray, byte>
- median_bg: float
- median_fg: float
- d_fg: Image<Gray, float32> } // Euclidean distances of the foreground to median_fg.
-
-let kmedians (img: Image<Gray, float32>) : Result =
+type Result =
+ {
+ fg : Image<Gray, byte>
+ median_bg : float
+ median_fg : float
+ d_fg : Image<Gray, float32> // Euclidean distances of the foreground to median_fg.
+ }
+
+let kmedians (img : Image<Gray, float32>) : Result =
let nbIteration = 4
let w = img.Width
let h = img.Height
let min = ref [| 0.0 |]
- let minLocation = ref <| [| Point() |]
+ let minLocation = ref <| [| Point () |]
let max = ref [| 0.0 |]
- let maxLocation = ref <| [| Point() |]
- img.MinMax(min, max, minLocation, maxLocation)
+ let maxLocation = ref <| [| Point () |]
+ img.MinMax (min, max, minLocation, maxLocation)
let mutable median_bg = (!max).[0] - ((!max).[0] - (!min).[0]) / 4.0
let mutable median_fg = (!min).[0] + ((!max).[0] - (!min).[0]) / 4.0
- use mutable d_bg = new Image<Gray, float32>(img.Size)
- let mutable d_fg = new Image<Gray, float32>(img.Size)
- let mutable fg = new Image<Gray, byte>(img.Size)
+ use mutable d_bg = new Image<Gray, float32> (img.Size)
+ let mutable d_fg = new Image<Gray, float32> (img.Size)
+ let mutable fg = new Image<Gray, byte> (img.Size)
for i = 1 to nbIteration do
- d_bg <- img.AbsDiff(Gray(median_bg))
- d_fg <- img.AbsDiff(Gray(median_fg))
+ d_bg <- img.AbsDiff (Gray median_bg)
+ d_fg <- img.AbsDiff (Gray median_fg)
- CvInvoke.Compare(d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
+ CvInvoke.Compare (d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
- let bg_values = List<float>()
- let fg_values = List<float>()
+ let bg_values = List<float> ()
+ let fg_values = List<float> ()
for i = 0 to h - 1 do
for j = 0 to w - 1 do
- if fg.Data.[i, j, 0] > 0uy
- then fg_values.Add(float img.Data.[i, j, 0])
- else bg_values.Add(float img.Data.[i, j, 0])
+ if fg.Data.[i, j, 0] > 0uy then
+ fg_values.Add (float img.Data.[i, j, 0])
+ else
+ bg_values.Add (float img.Data.[i, j, 0])
- median_bg <- MathNet.Numerics.Statistics.Statistics.Median(bg_values)
- median_fg <- MathNet.Numerics.Statistics.Statistics.Median(fg_values)
+ median_bg <- MathNet.Numerics.Statistics.Statistics.Median bg_values
+ median_fg <- MathNet.Numerics.Statistics.Statistics.Median fg_values
{ fg = fg; median_bg = median_bg; median_fg = median_fg; d_fg = d_fg }