X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FImgTools.fs;h=f567e682decb86c97b81aefeb8c7a44eeab1f347;hp=2f021c8ae04a8a60e429a52b4da7f192b24c2546;hb=bef2e9f0bf1bba21d4c988fdf654c2dc303ec34a;hpb=f9ee9f2c0c1194a6a8f7475ee2ca0b7076b32261 diff --git a/Parasitemia/Parasitemia/ImgTools.fs b/Parasitemia/Parasitemia/ImgTools.fs index 2f021c8..f567e68 100644 --- a/Parasitemia/Parasitemia/ImgTools.fs +++ b/Parasitemia/Parasitemia/ImgTools.fs @@ -21,6 +21,124 @@ let normalizeAndConvert (img: Image) : Image = ((img - (!min).[0]) / ((!max).[0] - (!min).[0]) * 255.0).Convert() +let saveImg (img: Image<'TColor, 'TDepth>) (filepath: string) = + img.Save(filepath) + + +let saveMat (mat: Matrix<'TDepth>) (filepath: string) = + use img = new Image(mat.Size) + mat.CopyTo(img) + saveImg img filepath + + +let suppressMConnections (img: Matrix) = + 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) : Matrix * Image * Image = + 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() + let yGradient = img.Convolution(sobelKernel.Transpose()).Convert() + + 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(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() + 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(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(xGradient.Size) + + // Histeresis thresholding. + let toVisit = Stack() + 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) @@ -32,7 +150,6 @@ let drawPoints (img: Image) (points: Points) (intensity: byte) = for p in points do img.Data.[p.Y, p.X, 0] <- intensity - type ExtremumType = | Maxima = 1 | Minima = 2 @@ -356,6 +473,7 @@ let areaOpen (img: Image) (area: int) = let areaClose (img: Image) (area: int) = areaOperation img area AreaOperation.Closing +// A simpler algorithm than 'areaOpen' but slower. let areaOpen2 (img: Image) (area: int) = let w = img.Width let h = img.Height @@ -537,21 +655,14 @@ let connectedComponents (img: Image) (startPoints: List) : Li List(pointChecked) -let saveImg (img: Image<'TColor, 'TDepth>) (filepath: string) = - img.Save(filepath) - - -let saveMat (mat: Matrix<'TDepth>) (filepath: string) = - use img = new Image(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