1
module ParasitemiaCore.KMeans
3 open System.Collections.Generic
11 fg
: Image<Gray, byte
>
14 d_fg
: Image<Gray, float32
> // Euclidean distances of the foreground to mean_fg.
17 let kmeans (img
: Image<Gray, float32
>) : Result =
22 let min = ref [| 0.0
|]
23 let minLocation = ref <| [| Point () |]
24 let max = ref [| 0.0
|]
25 let maxLocation = ref <| [| Point () |]
26 img
.MinMax (min, max, minLocation, maxLocation)
28 let minf = float32
(!min).[0]
29 let maxf = float32
(!max).[0]
31 let mutable mean_bg = maxf - (maxf - minf) / 4.f
32 let mutable mean_fg = minf + (maxf - minf) / 4.f
33 use mutable d_bg : Image<Gray, float32
> = null
34 let mutable d_fg : Image<Gray, float32
> = null
35 let fg = new Image<Gray, byte
> (img
.Size)
37 let imgData = img
.Data
40 for i
= 1 to nbIteration do
47 // EmGu doesn't import the in-place version of 'AbsDiff' so we have to create two images for each iteration.
48 d_bg <- img
.AbsDiff (Gray (float mean_bg))
49 d_fg <- img
.AbsDiff (Gray (float mean_fg))
51 CvInvoke.Compare (d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
53 let mutable bg_total = 0.f
56 let mutable fg_total = 0.f
61 if fgData.[i
, j
, 0] > 0uy then
62 fg_total <- fg_total + imgData.[i
, j
, 0]
65 bg_total <- bg_total + imgData.[i
, j
, 0]
68 mean_bg <- bg_total / float32
bg_nb
69 mean_fg <- fg_total / float32
fg_nb
71 { fg = fg; mean_bg = mean_bg; mean_fg = mean_fg; d_fg = d_fg }