open System
open System.Drawing
open System.Collections.Generic
+open System.Linq
open Emgu.CV
open Emgu.CV.Structure
open Utils
+open Heap
// Normalize image values between 0uy and 255uy.
let normalizeAndConvert (img: Image<Gray, float32>) : Image<Gray, byte> =
img.MinMax(min, max, minLocation, maxLocation)
((img - (!min).[0]) / ((!max).[0] - (!min).[0]) * 255.0).Convert<Gray, byte>()
+
+let saveImg (img: Image<'TColor, 'TDepth>) (filepath: string) =
+ img.Save(filepath)
+
+
+let saveMat (mat: Matrix<'TDepth>) (filepath: string) =
+ use img = new Image<Gray, 'TDeph>(mat.Size)
+ mat.CopyTo(img)
+ saveImg img filepath
+
+
+let suppressMConnections (img: Matrix<byte>) =
+ let w = img.Width
+ let h = img.Height
+ for i in 1 .. h - 2 do
+ for j in 1 .. w - 2 do
+ if img.[i, j] > 0uy && img.Data.[i + 1, j] > 0uy && (img.Data.[i, j - 1] > 0uy && img.Data.[i - 1, j + 1] = 0uy || img.Data.[i, j + 1] > 0uy && img.Data.[i - 1, j - 1] = 0uy) then
+ img.[i, j] <- 0uy
+ for i in 1 .. h - 2 do
+ for j in 1 .. w - 2 do
+ if img.[i, j] > 0uy && img.Data.[i - 1, j] > 0uy && (img.Data.[i, j - 1] > 0uy && img.Data.[i + 1, j + 1] = 0uy || img.Data.[i, j + 1] > 0uy && img.Data.[i + 1, j - 1] = 0uy) then
+ img.[i, j] <- 0uy
+
+let findEdges (img: Image<Gray, float32>) : Matrix<byte> * Image<Gray, float> * Image<Gray, float> =
+ let w = img.Width
+ let h = img.Height
+
+ use sobelKernel =
+ new ConvolutionKernelF(array2D [[ 1.0f; 0.0f; -1.0f ]
+ [ 2.0f; 0.0f; -2.0f ]
+ [ 1.0f; 0.0f; -1.0f ]], Point(1, 1))
+
+ let xGradient = img.Convolution(sobelKernel).Convert<Gray, float>()
+ let yGradient = img.Convolution(sobelKernel.Transpose()).Convert<Gray, float>()
+
+ let xGradientData = xGradient.Data
+ let yGradientData = yGradient.Data
+ for r in 0 .. h - 1 do
+ xGradientData.[r, 0, 0] <- 0.0
+ xGradientData.[r, w - 1, 0] <- 0.0
+ yGradientData.[r, 0, 0] <- 0.0
+ yGradientData.[r, w - 1, 0] <- 0.0
+
+ for c in 0 .. w - 1 do
+ xGradientData.[0, c, 0] <- 0.0
+ xGradientData.[h - 1, c, 0] <- 0.0
+ yGradientData.[0, c, 0] <- 0.0
+ yGradientData.[h - 1, c, 0] <- 0.0
+
+ use magnitudes = new Matrix<float>(xGradient.Size)
+ CvInvoke.CartToPolar(xGradient, yGradient, magnitudes, new Mat()) // Compute the magnitudes (without angles).
+
+ let thresholdHigh, thresholdLow =
+ let sensibility = 0.1
+ use magnitudesByte = magnitudes.Convert<byte>()
+ let threshold = CvInvoke.Threshold(magnitudesByte, magnitudesByte, 0.0, 1.0, CvEnum.ThresholdType.Otsu ||| CvEnum.ThresholdType.Binary)
+ threshold + (sensibility * threshold), threshold - (sensibility * threshold)
+
+ // Non-maximum suppression.
+ use nms = new Matrix<byte>(xGradient.Size)
+ nms.SetValue(1.0)
+
+ for i in 0 .. h - 1 do
+ nms.Data.[i, 0] <- 0uy
+ nms.Data.[i, w - 1] <- 0uy
+
+ for j in 0 .. w - 1 do
+ nms.Data.[0, j] <- 0uy
+ nms.Data.[h - 1, j] <- 0uy
+
+ for i in 1 .. h - 2 do
+ for j in 1 .. w - 2 do
+ let vx = xGradient.Data.[i, j, 0]
+ let vy = yGradient.Data.[i, j, 0]
+ let angle =
+ let a = atan2 vy vx
+ if a < 0.0 then 2. * Math.PI + a else a
+
+ let mNeigbors (sign: int) : float =
+ if angle < Math.PI / 8. || angle >= 15.0 * Math.PI / 8. then magnitudes.Data.[i, j + sign]
+ elif angle < 3.0 * Math.PI / 8. then magnitudes.Data.[i + sign, j + sign]
+ elif angle < 5.0 * Math.PI / 8. then magnitudes.Data.[i + sign, j]
+ elif angle < 7.0 * Math.PI / 8. then magnitudes.Data.[i + sign, j - sign]
+ elif angle < 9.0 * Math.PI / 8. then magnitudes.Data.[i, j - sign]
+ elif angle < 11.0 * Math.PI / 8. then magnitudes.Data.[i - sign, j - sign]
+ elif angle < 13.0 * Math.PI / 8. then magnitudes.Data.[i - sign, j]
+ else magnitudes.Data.[i - sign, j + sign]
+
+ let m = magnitudes.Data.[i, j]
+ if m < mNeigbors 1 || m < mNeigbors -1 || m < thresholdLow then
+ nms.Data.[i, j] <- 0uy
+
+ // suppressMConnections nms // It's not usefull for the rest of the process (ellipse detection).
+
+ let edges = new Matrix<byte>(xGradient.Size)
+
+ // Histeresis thresholding.
+ let toVisit = Stack<Point>()
+ for i in 0 .. h - 1 do
+ for j in 0 .. w - 1 do
+ if nms.Data.[i, j] = 1uy && magnitudes.Data.[i, j] >= thresholdHigh then
+ nms.Data.[i, j] <- 0uy
+ toVisit.Push(Point(j, i))
+ while toVisit.Count > 0 do
+ let p = toVisit.Pop()
+ edges.Data.[p.Y, p.X] <- 1uy
+ for i' in -1 .. 1 do
+ for j' in -1 .. 1 do
+ if i' <> 0 || j' <> 0 then
+ let ni = p.Y + i'
+ let nj = p.X + j'
+ if ni >= 0 && ni < h && nj >= 0 && nj < w && nms.Data.[ni, nj] = 1uy then
+ nms.Data.[ni, nj] <- 0uy
+ toVisit.Push(Point(nj, ni))
+
+
+ edges, xGradient, yGradient
+
+
let gaussianFilter (img : Image<'TColor, 'TDepth>) (standardDeviation : float) : Image<'TColor, 'TDepth> =
let size = 2 * int (ceil (4.0 * standardDeviation)) + 1
img.SmoothGaussian(size, size, standardDeviation, standardDeviation)
+
+type Points = HashSet<Point>
+
+let drawPoints (img: Image<Gray, byte>) (points: Points) (intensity: byte) =
+ for p in points do
+ img.Data.[p.Y, p.X, 0] <- intensity
+
+type ExtremumType =
+ | Maxima = 1
+ | Minima = 2
+
+let findExtremum (img: Image<Gray, byte>) (extremumType: ExtremumType) : IEnumerable<Points> =
+ let w = img.Width
+ let h = img.Height
+ let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |]
+
+ let imgData = img.Data
+ let suppress: bool[,] = Array2D.zeroCreate h w
+
+ let result = List<List<Point>>()
+
+ let flood (start: Point) : List<List<Point>> =
+ let sameLevelToCheck = Stack<Point>()
+ let betterLevelToCheck = Stack<Point>()
+ betterLevelToCheck.Push(start)
+
+ let result' = List<List<Point>>()
+
+ while betterLevelToCheck.Count > 0 do
+ let p = betterLevelToCheck.Pop()
+ if not suppress.[p.Y, p.X]
+ then
+ suppress.[p.Y, p.X] <- true
+ sameLevelToCheck.Push(p)
+ let current = List<Point>()
+
+ let mutable betterExists = false
+
+ while sameLevelToCheck.Count > 0 do
+ let p' = sameLevelToCheck.Pop()
+ let currentLevel = imgData.[p'.Y, p'.X, 0]
+ current.Add(p') |> ignore
+ for i, j in se do
+ let ni = i + p'.Y
+ let nj = j + p'.X
+ if ni >= 0 && ni < h && nj >= 0 && nj < w
+ then
+ let level = imgData.[ni, nj, 0]
+ let notSuppressed = not suppress.[ni, nj]
+
+ if level = currentLevel && notSuppressed
+ then
+ suppress.[ni, nj] <- true
+ sameLevelToCheck.Push(Point(nj, ni))
+ elif if extremumType = ExtremumType.Maxima then level > currentLevel else level < currentLevel
+ then
+ betterExists <- true
+ if notSuppressed
+ then
+ betterLevelToCheck.Push(Point(nj, ni))
+
+ if not betterExists
+ then
+ result'.Add(current)
+ result'
+
+ for i in 0 .. h - 1 do
+ for j in 0 .. w - 1 do
+ let maxima = flood (Point(j, i))
+ if maxima.Count > 0
+ then
+ result.AddRange(maxima)
+
+ result.Select(fun l -> Points(l))
+
+
+let findMaxima (img: Image<Gray, byte>) : IEnumerable<Points> =
+ findExtremum img ExtremumType.Maxima
+
+let findMinima (img: Image<Gray, byte>) : IEnumerable<Points> =
+ findExtremum img ExtremumType.Minima
+
+
+type PriorityQueue () =
+ let size = 256
+ let q: Points[] = Array.init size (fun i -> Points())
+ let mutable highest = -1 // Value of the first elements of 'q'.
+ let mutable lowest = size
+
+ member this.NextMax () : byte * Point =
+ if this.IsEmpty
+ then
+ invalidOp "Queue is empty"
+ else
+ let l = q.[highest]
+ let next = l.First()
+ l.Remove(next) |> ignore
+ let value = byte highest
+
+ if l.Count = 0
+ then
+ highest <- highest - 1
+ while highest > lowest && q.[highest].Count = 0 do
+ highest <- highest - 1
+ if highest = lowest
+ then
+ highest <- -1
+ lowest <- size
+
+ value, next
+
+ member this.NextMin () : byte * Point =
+ if this.IsEmpty
+ then
+ invalidOp "Queue is empty"
+ else
+ let l = q.[lowest + 1]
+ let next = l.First()
+ l.Remove(next) |> ignore
+ let value = byte (lowest + 1)
+
+ if l.Count = 0
+ then
+ lowest <- lowest + 1
+ while lowest < highest && q.[lowest + 1].Count = 0 do
+ lowest <- lowest + 1
+ if highest = lowest
+ then
+ highest <- -1
+ lowest <- size
+
+ value, next
+
+ member this.Max =
+ highest |> byte
+
+ member this.Min =
+ lowest + 1 |> byte
+
+ member this.Add (value: byte) (p: Point) =
+ let vi = int value
+
+ if vi > highest
+ then
+ highest <- vi
+ if vi <= lowest
+ then
+ lowest <- vi - 1
+
+ q.[vi].Add(p) |> ignore
+
+ member this.Remove (value: byte) (p: Point) =
+ let vi = int value
+ if q.[vi].Remove(p) && q.[vi].Count = 0
+ then
+ if vi = highest
+ then
+ highest <- highest - 1
+ while highest > lowest && q.[highest].Count = 0 do
+ highest <- highest - 1
+ elif vi - 1 = lowest
+ then
+ lowest <- lowest + 1
+ while lowest < highest && q.[lowest + 1].Count = 0 do
+ lowest <- lowest + 1
+
+ if highest = lowest // The queue is now empty.
+ then
+ highest <- -1
+ lowest <- size
+
+ member this.IsEmpty =
+ highest = -1
+
+ member this.Clear () =
+ while highest > lowest do
+ q.[highest].Clear()
+ highest <- highest - 1
+ highest <- -1
+ lowest <- size
+
+
+type private AreaState =
+ | Removed = 1
+ | Unprocessed = 2
+ | Validated = 3
+
+type private AreaOperation =
+ | Opening = 1
+ | Closing = 2
+
+[<AllowNullLiteral>]
+type private Area (elements: Points) =
+ member this.Elements = elements
+ member val Intensity = None with get, set
+ member val State = AreaState.Unprocessed with get, set
+
+let private areaOperation (img: Image<Gray, byte>) (area: int) (op: AreaOperation) =
+ let w = img.Width
+ let h = img.Height
+ let imgData = img.Data
+ let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |]
+
+ let areas = List<Area>((if op = AreaOperation.Opening then findMaxima img else findMinima img) |> Seq.map Area)
+
+ let pixels: Area[,] = Array2D.create h w null
+ for m in areas do
+ for e in m.Elements do
+ pixels.[e.Y, e.X] <- m
+
+ let queue = PriorityQueue()
+
+ let addEdgeToQueue (elements: Points) =
+ for p in elements do
+ for i, j in se do
+ let ni = i + p.Y
+ let nj = j + p.X
+ let p' = Point(nj, ni)
+ if ni >= 0 && ni < h && nj >= 0 && nj < w && not (elements.Contains(p'))
+ then
+ queue.Add (imgData.[ni, nj, 0]) p'
+
+ // Reverse order is quicker.
+ for i in areas.Count - 1 .. -1 .. 0 do
+ let m = areas.[i]
+ if m.Elements.Count <= area && m.State <> AreaState.Removed
+ then
+ queue.Clear()
+ addEdgeToQueue m.Elements
+
+ let mutable intensity = if op = AreaOperation.Opening then queue.Max else queue.Min
+ let nextElements = Points()
+
+ let mutable stop = false
+ while not stop do
+ let intensity', p = if op = AreaOperation.Opening then queue.NextMax () else queue.NextMin ()
+ let mutable merged = false
+
+ if intensity' = intensity // The intensity doesn't change.
+ then
+ if m.Elements.Count + nextElements.Count + 1 > area
+ then
+ m.State <- AreaState.Validated
+ m.Intensity <- Some intensity
+ stop <- true
+ else
+ nextElements.Add(p) |> ignore
+
+ elif if op = AreaOperation.Opening then intensity' < intensity else intensity' > intensity
+ then
+ m.Elements.UnionWith(nextElements)
+ for e in nextElements do
+ pixels.[e.Y, e.X] <- m
+
+ if m.Elements.Count = area
+ then
+ m.State <- AreaState.Validated
+ m.Intensity <- Some (intensity')
+ stop <- true
+ else
+ intensity <- intensity'
+ nextElements.Clear()
+ nextElements.Add(p) |> ignore
+
+ else
+ let m' = pixels.[p.Y, p.X]
+ if m' <> null
+ then
+ if m'.Elements.Count + m.Elements.Count <= area
+ then
+ m'.State <- AreaState.Removed
+ for e in m'.Elements do
+ pixels.[e.Y, e.X] <- m
+ queue.Remove imgData.[e.Y, e.X, 0] e
+ addEdgeToQueue m'.Elements
+ m.Elements.UnionWith(m'.Elements)
+ let intensityMax = if op = AreaOperation.Opening then queue.Max else queue.Min
+ if intensityMax <> intensity
+ then
+ intensity <- intensityMax
+ nextElements.Clear()
+ merged <- true
+
+ if not merged
+ then
+ m.State <- AreaState.Validated
+ m.Intensity <- Some (intensity)
+ stop <- true
+
+ if not stop && not merged
+ then
+ for i, j in se do
+ let ni = i + p.Y
+ let nj = j + p.X
+ let p' = Point(nj, ni)
+ if ni < 0 || ni >= h || nj < 0 || nj >= w
+ then
+ m.State <- AreaState.Validated
+ m.Intensity <- Some (intensity)
+ stop <- true
+ elif not (m.Elements.Contains(p')) && not (nextElements.Contains(p'))
+ then
+ queue.Add (imgData.[ni, nj, 0]) p'
+
+ if queue.IsEmpty
+ then
+ if m.Elements.Count + nextElements.Count <= area
+ then
+ m.State <- AreaState.Validated
+ m.Intensity <- Some intensity'
+ m.Elements.UnionWith(nextElements)
+ stop <- true
+
+ for m in areas do
+ if m.State = AreaState.Validated
+ then
+ match m.Intensity with
+ | Some i ->
+ for p in m.Elements do
+ imgData.[p.Y, p.X, 0] <- i
+ | _ -> ()
+ ()
+
+
+let areaOpen (img: Image<Gray, byte>) (area: int) =
+ areaOperation img area AreaOperation.Opening
+
+let areaClose (img: Image<Gray, byte>) (area: int) =
+ areaOperation img area AreaOperation.Closing
+
+// A simpler algorithm than 'areaOpen' but slower.
+let areaOpen2 (img: Image<Gray, byte>) (area: int) =
+ let w = img.Width
+ let h = img.Height
+ let imgData = img.Data
+ let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |]
+
+ let histogram = Array.zeroCreate 256
+ for i in 0 .. h - 1 do
+ for j in 0 .. w - 1 do
+ let v = imgData.[i, j, 0] |> int
+ histogram.[v] <- histogram.[v] + 1
+
+ let flooded : bool[,] = Array2D.zeroCreate h w
+
+ let pointsChecked = HashSet<Point>()
+ let pointsToCheck = Stack<Point>()
+
+ for level in 255 .. -1 .. 0 do
+ let mutable n = histogram.[level]
+ if n > 0
+ then
+ for i in 0 .. h - 1 do
+ for j in 0 .. w - 1 do
+ if not flooded.[i, j] && imgData.[i, j, 0] = byte level
+ then
+ let mutable maxNeighborValue = 0uy
+ pointsChecked.Clear()
+ pointsToCheck.Clear()
+ pointsToCheck.Push(Point(j, i))
+
+ while pointsToCheck.Count > 0 do
+ let next = pointsToCheck.Pop()
+ pointsChecked.Add(next) |> ignore
+ flooded.[next.Y, next.X] <- true
+
+ for nx, ny in se do
+ let p = Point(next.X + nx, next.Y + ny)
+ if p.X >= 0 && p.X < w && p.Y >= 0 && p.Y < h
+ then
+ let v = imgData.[p.Y, p.X, 0]
+ if v = byte level
+ then
+ if not (pointsChecked.Contains(p))
+ then
+ pointsToCheck.Push(p)
+ elif v > maxNeighborValue
+ then
+ maxNeighborValue <- v
+
+ if int maxNeighborValue < level && pointsChecked.Count <= area
+ then
+ for p in pointsChecked do
+ imgData.[p.Y, p.X, 0] <- maxNeighborValue
+
+
// Zhang and Suen algorithm.
// Modify 'mat' in place.
let thin (mat: Matrix<byte>) =
data2 <- tmp
+// FIXME: replace by a queue or stack.
let pop (l: List<'a>) : 'a =
let n = l.[l.Count - 1]
l.RemoveAt(l.Count - 1)
let w = img.Width
let h = img.Height
- let pointChecked = HashSet<Point>()
+ let pointChecked = Points()
let pointToCheck = List<Point>(startPoints);
let data = img.Data
List<Point>(pointChecked)
-let saveImg (img: Image<'TColor, 'TDepth>) (filepath: string) =
- img.Save(filepath)
-
-
-let saveMat (mat: Matrix<'TDepth>) (filepath: string) =
- use img = new Image<Gray, 'TDeph>(mat.Size)
- mat.CopyTo(img)
- saveImg img filepath
-
let drawLine (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: int) (y0: int) (x1: int) (y1: int) (thickness: int) =
img.Draw(LineSegment2D(Point(x0, y0), Point(x1, y1)), color, thickness);
+
let drawLineF (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: float) (y0: float) (x1: float) (y1: float) (thickness: int) =
img.Draw(LineSegment2DF(PointF(float32 x0, float32 y0), PointF(float32 x1, float32 y1)), color, thickness, CvEnum.LineType.AntiAlias);
+
let drawEllipse (img: Image<'TColor, 'TDepth>) (e: Types.Ellipse) (color: 'TColor) (alpha: float) =
if alpha >= 1.0
projects / master-thesis.git / blobdiff