/// <summary>
/// add two images
/// </summary>
/// <param name="img">
/// ref Image
/// </param>
/// <param name="summand">
/// image to add
/// </param>
public static void Add(ref ImageData img, ImageData summand)
{
if((img.Width == summand.Width) && (img.Height == summand.Height))
{
for(int column = 0; column < summand.Width; column++)
{
for(int row = 0; row < summand.Height; row++)
{
Color a = summand[column, row];
Color b = img[column, row];
int cr = a.R + b.R;
int cg = a.G + b.G;
int cb = a.B + b.B;
if(cr > 255)
{
cr -= 255;
}
if(cg > 255)
{
cg -= 255;
}
if(cb > 255)
{
cb -= 255;
}
img[column, row] = Color.FromArgb(cr, cg, cb);
}
}
}
}
/// <summary>
/// Get the average rgb-values from an image in a given rectangle
/// By default the function calculate the average rgb-values from the whole image
/// </summary>
/// <param name="img">
/// Image
/// </param>
/// <param name="left">
/// left of rectangle (default=0)
/// </param>
/// <param name="top">
/// top of rectangle (default=0)
/// </param>
/// <param name="width">
/// width of rectangle (default=full width)
/// </param>
/// <param name="height">
/// height of rectangle (default=full height)
/// </param>
/// <returns>
/// averag rgb-values
/// </returns>
public static double[] AverageRgbValues(ImageData img, int left = 0, int top = 0, int width = -1, int height = -1)
{
long[] totals = { 0, 0, 0 };
if(width == -1)
{
width = img.Width;
}
if(height == -1)
{
height = img.Height;
}
for(int x = left; x < left + width; x++)
{
for(int y = top; y < top + height; y++)
{
Color currentColor = img.GetPixel(x, y);
totals[0] += currentColor.R;
totals[1] += currentColor.G;
totals[2] += currentColor.B;
}
}
int count = width * height;
double[] retvar = { totals[0] / (double)count, totals[1] / (double)count, totals[2] / (double)count };
return retvar;
}
/// <summary>
/// search for an image in another image
/// return all possible matchings
/// </summary>
/// <param name="img">
/// image to look in
/// </param>
/// <param name="Ref">
/// image to look for
/// </param>
/// <param name="tolerance">
/// tolerance of similarity (0,...,255)
/// </param>
/// <returns>
/// List of matching positions (datatype Rectange)
/// </returns>
public static List<Rectangle> AllImages(ImageData img, ImageData Ref, uint tolerance = 0)
{
List<Rectangle> retVal = new List<Rectangle>();
for(int originalX = 0; originalX < img.Width - Ref.Width; originalX++)
{
for(int originalY = 0; originalY < img.Height - Ref.Height; originalY++)
{
Color currentInnerPictureColor = Ref[0, 0];
Color currentOuterPictureColor = img[originalX, originalY];
if(!CommonFunctions.ColorsSimilar(currentInnerPictureColor, currentOuterPictureColor, tolerance))
{
continue;
}
bool allSimilar = true;
for(int referenceX = 0; referenceX < Ref.Width; referenceX++)
{
if(!allSimilar)
{
break;
}
for(int referenceY = 0; referenceY < Ref.Height; referenceY++)
{
if(!allSimilar)
{
break;
}
currentInnerPictureColor = Ref[referenceX, referenceY];
currentOuterPictureColor = img[originalX + referenceX, originalY + referenceY];
if(!CommonFunctions.ColorsSimilar(currentInnerPictureColor, currentOuterPictureColor, tolerance))
{
allSimilar = false;
}
}
}
if(allSimilar)
{
retVal.Add(new Rectangle(originalX, originalY, Ref.Width, Ref.Height));
}
}
}
return retVal;
}
/// <summary>
/// sharpen an image
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
/// <param name="weight">
/// weight
/// </param>
public static void Sharpen(ref ImageData img, double weight)
{
ConvolutionMatrix cMatrix = new ConvolutionMatrix(3);
cMatrix.SetAll(1);
cMatrix.Matrix[0, 0] = 0;
cMatrix.Matrix[1, 0] = -2;
cMatrix.Matrix[2, 0] = 0;
cMatrix.Matrix[0, 1] = -2;
cMatrix.Matrix[1, 1] = weight;
cMatrix.Matrix[2, 1] = -2;
cMatrix.Matrix[0, 2] = 0;
cMatrix.Matrix[1, 2] = -2;
cMatrix.Matrix[2, 2] = 0;
cMatrix.Factor = weight - 8;
ApplyConvolution3X3(ref img, cMatrix);
}
/// <summary>
/// Convert image to sepia
/// </summary>
/// <param name="img">
/// ref image to convert
/// </param>
public static void Sepia(ref ImageData img)
{
for(int column = 0; column < img.Width; column++)
{
for(int row = 0; row < img.Height; row++)
{
Color c = img[column, row];
int t = Convert.ToInt32(0.299 * c.R + 0.587 * c.G + 0.114 * c.B);
img.SetPixel(column, row, Color.FromArgb((t > 206) ? 255 : t + 49, (t < 14) ? 0 : t - 14, (t < 56) ? 0 : t - 56));
}
}
}
/// <summary>
/// search for an image in another image
/// return the best matching position
/// </summary>
/// <param name="img">
/// image to look in
/// </param>
/// <param name="Ref">
/// image to look for
/// </param>
/// <param name="tolerance">
/// tolerance of similarity (0,...,255)
/// </param>
/// <returns>
/// best matching position as rectangle
/// </returns>
public static Rectangle Image(ImageData img, ImageData Ref, uint tolerance = 0)
{
double bestScore = Math.Abs(byte.MaxValue - byte.MinValue) * 3;
Point location = Point.Empty;
bool found = false;
for(int originalX = 0; originalX < img.Width - Ref.Width; originalX++)
{
for(int originalY = 0; originalY < img.Height - Ref.Height; originalY++)
{
Color currentInnerPictureColor = Ref[0, 0];
Color currentOuterPictureColor = img[originalX, originalY];
if(!CommonFunctions.ColorsSimilar(currentInnerPictureColor, currentOuterPictureColor, tolerance))
{
continue;
}
int currentScore = 0;
bool allSimilar = true;
for(int referenceX = 0; referenceX < Ref.Width; referenceX++)
{
if(!allSimilar)
{
break;
}
for(int referenceY = 0; referenceY < Ref.Height; referenceY++)
{
if(!allSimilar)
{
break;
}
currentInnerPictureColor = Ref[referenceX, referenceY];
currentOuterPictureColor = img[originalX + referenceX, originalY + referenceY];
if(!CommonFunctions.ColorsSimilar(currentInnerPictureColor, currentOuterPictureColor, tolerance))
{
allSimilar = false;
}
currentScore += Math.Abs(currentInnerPictureColor.R - currentOuterPictureColor.R)
+ Math.Abs(currentInnerPictureColor.G - currentOuterPictureColor.G)
+ Math.Abs(currentInnerPictureColor.B - currentOuterPictureColor.B);
}
}
if(allSimilar)
{
if((currentScore / (double)(Ref.Width * Ref.Height)) < bestScore)
{
location.X = originalX;
location.Y = originalY;
bestScore = currentScore / (double)(Ref.Width * Ref.Height);
found = true;
}
}
}
}
return found ? new Rectangle(location.X, location.Y, Ref.Width, Ref.Height) : Rectangle.Empty;
}
/// <summary>
/// Get the average color from an image in a given rectangle
/// By default the function calculate the average color from the whole image
/// </summary>
/// <param name="img">
/// Image
/// </param>
/// <param name="left">
/// left of rectangle (default=0)
/// </param>
/// <param name="top">
/// top of rectangle (default=0)
/// </param>
/// <param name="width">
/// width of rectangle (default=full width)
/// </param>
/// <param name="height">
/// height of rectangle (default=full height)
/// </param>
/// <returns>
/// average color
/// </returns>
public static Color AverageColor(ImageData img, int left = 0, int top = 0, int width = -1, int height = -1)
{
double[] retvar = AverageRgbValues(img, left, top, width, height);
return Color.FromArgb(Convert.ToInt32(retvar[0]), Convert.ToInt32(retvar[1]), Convert.ToInt32(retvar[2]));
}
/// <summary>
/// identify image from list (choose the image with best matching)
/// </summary>
/// <param name="img">
/// image to look for
/// </param>
/// <param name="statReference">
/// list of reference images
/// </param>
/// <returns>
/// name (key of list)
/// </returns>
public static string IdentifyImage(ImageData img, Dictionary<string, ImageData> statReference)
{
double similar = 0.0;
string keyword = string.Empty;
foreach(KeyValuePair<string, ImageData> item in statReference)
{
// exakte übereinstimmung der Größen ermöglicht einen simplen vergleich
if((img.Width == item.Value.Width) && (img.Height == item.Value.Height))
{
double s = Similarity(img, item.Value);
if(s > similar)
{
keyword = item.Key;
similar = s;
}
}
else
{
if((img.Width > item.Value.Width) && (img.Height > item.Value.Height))
{
// im größeren suchen
for(int column = 0; column < img.Width - item.Value.Width; column++)
{
for(int row = 0; row < img.Height - item.Value.Height; row++)
{
double s = Similarity(img, item.Value, 0, 0, item.Value.Width, item.Value.Height, column, row);
if(s > similar)
{
keyword = item.Key;
similar = s;
}
}
}
}
}
}
return keyword;
}
/// <summary>
/// change the brightness of an image
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
/// <param name="brightness">
/// brightness of new image
/// </param>
public static void Brightness(ref ImageData img, int brightness)
{
for(int y = 0; y < img.Height; y++)
{
for(int x = 0; x < img.Width; x++)
{
Color pixelColor = img[x, y];
int redChannel = pixelColor.R + brightness;
int greenChannel = pixelColor.G + brightness;
int blueChannel = pixelColor.B + brightness;
redChannel = (redChannel > 255) ? 255 : redChannel;
redChannel = (redChannel < 0) ? 0 : redChannel;
greenChannel = (greenChannel > 255) ? 255 : greenChannel;
greenChannel = (greenChannel < 0) ? 0 : greenChannel;
blueChannel = (blueChannel > 255) ? 255 : blueChannel;
blueChannel = (blueChannel < 0) ? 0 : blueChannel;
img.SetPixel(x, y, Color.FromArgb(redChannel, greenChannel, blueChannel));
}
}
}
/// <summary>
/// black and white image by replace
/// all similar color to black by blackand
/// all similiar colors to white by white
/// </summary>
/// <param name="img">
/// ref image
/// </param>
/// <param name="tolerance">
/// tolerance (0,...,255)
/// </param>
public static void BlackAndWhite(ref ImageData img, uint tolerance)
{
ReplaceSimilarColor(ref img, Color.Black, Color.Black, tolerance);
ReplaceDifferentColor(ref img, Color.Black, Color.White, tolerance);
}
/// <summary>
/// apply gaussianblur to image
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
/// <param name="peakValue">
/// parameter
/// </param>
public static void GaussianBlur(ref ImageData img, double peakValue)
{
ConvolutionMatrix cMatrix = new ConvolutionMatrix(3);
cMatrix.SetAll(1);
cMatrix.Matrix[0, 0] = peakValue / 4;
cMatrix.Matrix[1, 0] = peakValue / 2;
cMatrix.Matrix[2, 0] = peakValue / 4;
cMatrix.Matrix[0, 1] = peakValue / 2;
cMatrix.Matrix[1, 1] = peakValue;
cMatrix.Matrix[2, 1] = peakValue / 2;
cMatrix.Matrix[0, 2] = peakValue / 4;
cMatrix.Matrix[1, 2] = peakValue / 2;
cMatrix.Matrix[2, 2] = peakValue / 4;
cMatrix.Factor = peakValue * 4;
ApplyConvolution3X3(ref img, cMatrix);
}
/// <summary>
/// marks the edges black and all other pixels white
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
public static void FindEdges(ref ImageData img)
{
Emboss(ref img, 4.0);
ReplaceSimilarColor(ref img, Color.FromArgb(127, 132, 127), Color.White, 20);
ReplaceDifferentColor(ref img, Color.White, Color.Black, 1);
}
/// <summary>
/// apply emboss effect on image
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
/// <param name="weight">
/// weight of emboss effect
/// </param>
public static void Emboss(ref ImageData img, double weight)
{
ConvolutionMatrix cMatrix = new ConvolutionMatrix(3);
cMatrix.SetAll(1);
cMatrix.Matrix[0, 0] = -1;
cMatrix.Matrix[1, 0] = 0;
cMatrix.Matrix[2, 0] = -1;
cMatrix.Matrix[0, 1] = 0;
cMatrix.Matrix[1, 1] = weight;
cMatrix.Matrix[2, 1] = 0;
cMatrix.Matrix[0, 2] = -1;
cMatrix.Matrix[1, 2] = 0;
cMatrix.Matrix[2, 2] = -1;
cMatrix.Factor = 4;
cMatrix.Offset = 127;
ApplyConvolution3X3(ref img, cMatrix);
}
/// <summary>
/// subtract two images
/// </summary>
/// <param name="img">
/// ref images
/// </param>
/// <param name="subtrahend">
/// subtrahend
/// </param>
public static void Difference(ref ImageData img, ImageData subtrahend)
{
if((img.Width == subtrahend.Width) && (img.Height == subtrahend.Height))
{
for(int column = 0; column < subtrahend.Width; column++)
{
for(int row = 0; row < subtrahend.Height; row++)
{
Color a = subtrahend[column, row];
Color b = img[column, row];
int cr = a.R - b.R;
int cg = a.G - b.G;
int cb = a.B - b.B;
if(cr < 0)
{
cr += 255;
}
if(cg < 0)
{
cg += 255;
}
if(cb < 0)
{
cb += 255;
}
img[column, row] = Color.FromArgb(cr, cg, cb);
}
}
}
}
/// <summary>
/// decrease the depth of color
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
/// <param name="offset">
/// offset of colordepth
/// </param>
public static void DecreaseColourDepth(ref ImageData img, int offset)
{
for(int y = 0; y < img.Height; y++)
{
for(int x = 0; x < img.Width; x++)
{
Color pixelColor = img[x, y];
int redChannel = (pixelColor.R + (offset / 2)) - ((pixelColor.R + (offset / 2)) % offset) - 1;
int greenChannel = (pixelColor.G + (offset / 2)) - ((pixelColor.G + (offset / 2)) % offset) - 1;
int blueChannel = (pixelColor.B + (offset / 2)) - ((pixelColor.B + (offset / 2)) % offset) - 1;
redChannel = (redChannel < 0) ? 0 : redChannel;
greenChannel = (greenChannel < 0) ? 0 : greenChannel;
blueChannel = (blueChannel < 0) ? 0 : blueChannel;
img.SetPixel(x, y, Color.FromArgb(redChannel, greenChannel, blueChannel));
}
}
}
/// <summary>
/// change the contrast of an image
/// </summary>
/// <param name="img">
/// image to manipilate
/// </param>
/// <param name="contrast">
/// value of contrast
/// </param>
public static void Contrast(ref ImageData img, double contrast)
{
contrast = (100.0 + contrast) / 100.0;
contrast *= contrast;
for(int y = 0; y < img.Height; y++)
{
for(int x = 0; x < img.Width; x++)
{
Color pixelColor = img[x, y];
double redChannel = (((pixelColor.R / 255.0) - 0.5) * contrast + 0.5) * 255;
double greenChannel = (((pixelColor.G / 255.0) - 0.5) * contrast + 0.5) * 255;
double blueChannel = (((pixelColor.B / 255.0) - 0.5) * contrast + 0.5) * 255;
redChannel = (redChannel > 255) ? 255 : redChannel;
redChannel = (redChannel < 0) ? 0 : redChannel;
greenChannel = (greenChannel > 255) ? 255 : greenChannel;
greenChannel = (greenChannel < 0) ? 0 : greenChannel;
blueChannel = (blueChannel > 255) ? 255 : blueChannel;
blueChannel = (blueChannel < 0) ? 0 : blueChannel;
img.SetPixel(x, y, Color.FromArgb((int)redChannel, (int)greenChannel, (int)blueChannel));
}
}
}
/// <summary>
/// apply threshold
/// </summary>
/// <param name="img">
/// ref Image
/// </param>
/// <param name="threshold">
/// threshold (0,...,255)
/// </param>
public static void Threshold(ref ImageData img, uint threshold)
{
for(int column = 0; column < img.Width; column++)
{
for(int row = 0; row < img.Height; row++)
{
Color c = img[column, row];
if(c.R > threshold)
{
img[column, row] = Color.White;
}
else
{
img[column, row] = Color.Black;
}
}
}
}
/// <summary>
/// The apply convolution 3 x 3.
/// </summary>
/// <param name="img">
/// The img.
/// </param>
/// <param name="matrix">
/// The matrix.
/// </param>
private static void ApplyConvolution3X3(ref ImageData img, ConvolutionMatrix matrix)
{
ImageData newImg = img.Clone();
Color[,] pixelColor = new Color[3, 3];
for(int y = 0; y < img.Height - 2; y++)
{
for(int x = 0; x < img.Width - 2; x++)
{
pixelColor[0, 0] = img[x, y];
pixelColor[0, 1] = img[x, y + 1];
pixelColor[0, 2] = img[x, y + 2];
pixelColor[1, 0] = img[x + 1, y];
pixelColor[1, 1] = img[x + 1, y + 1];
pixelColor[1, 2] = img[x + 1, y + 2];
pixelColor[2, 0] = img[x + 2, y];
pixelColor[2, 1] = img[x + 2, y + 1];
pixelColor[2, 2] = img[x + 2, y + 2];
int alphaChannel = pixelColor[1, 1].A;
int redChannel =
(int)
((((pixelColor[0, 0].R * matrix.Matrix[0, 0]) + (pixelColor[1, 0].R * matrix.Matrix[1, 0])
+ (pixelColor[2, 0].R * matrix.Matrix[2, 0]) + (pixelColor[0, 1].R * matrix.Matrix[0, 1])
+ (pixelColor[1, 1].R * matrix.Matrix[1, 1]) + (pixelColor[2, 1].R * matrix.Matrix[2, 1])
+ (pixelColor[0, 2].R * matrix.Matrix[0, 2]) + (pixelColor[1, 2].R * matrix.Matrix[1, 2])
+ (pixelColor[2, 2].R * matrix.Matrix[2, 2])) / matrix.Factor) + matrix.Offset);
int greenChannel =
(int)
((((pixelColor[0, 0].G * matrix.Matrix[0, 0]) + (pixelColor[1, 0].G * matrix.Matrix[1, 0])
+ (pixelColor[2, 0].G * matrix.Matrix[2, 0]) + (pixelColor[0, 1].G * matrix.Matrix[0, 1])
+ (pixelColor[1, 1].G * matrix.Matrix[1, 1]) + (pixelColor[2, 1].G * matrix.Matrix[2, 1])
+ (pixelColor[0, 2].G * matrix.Matrix[0, 2]) + (pixelColor[1, 2].G * matrix.Matrix[1, 2])
+ (pixelColor[2, 2].G * matrix.Matrix[2, 2])) / matrix.Factor) + matrix.Offset);
int blueChannel =
(int)
((((pixelColor[0, 0].B * matrix.Matrix[0, 0]) + (pixelColor[1, 0].B * matrix.Matrix[1, 0])
+ (pixelColor[2, 0].B * matrix.Matrix[2, 0]) + (pixelColor[0, 1].B * matrix.Matrix[0, 1])
+ (pixelColor[1, 1].B * matrix.Matrix[1, 1]) + (pixelColor[2, 1].B * matrix.Matrix[2, 1])
+ (pixelColor[0, 2].B * matrix.Matrix[0, 2]) + (pixelColor[1, 2].B * matrix.Matrix[1, 2])
+ (pixelColor[2, 2].B * matrix.Matrix[2, 2])) / matrix.Factor) + matrix.Offset);
redChannel = (redChannel > 255) ? 255 : redChannel;
redChannel = (redChannel < 0) ? 0 : redChannel;
greenChannel = (greenChannel > 255) ? 255 : greenChannel;
greenChannel = (greenChannel < 0) ? 0 : greenChannel;
blueChannel = (blueChannel > 255) ? 255 : blueChannel;
blueChannel = (blueChannel < 0) ? 0 : blueChannel;
newImg.SetPixel(x + 1, y + 1, Color.FromArgb(alphaChannel, redChannel, greenChannel, blueChannel));
}
}
img = newImg.Clone();
}
/// <summary>
/// Initializes a new instance of the <see cref="ImageData" /> class.
/// creates a new imagedata object from another imagedata object
/// </summary>
/// <param name="img">
/// The Img.
/// </param>
public ImageData(ImageData img)
{
this.LoadBitmap(img.Bitmap);
}
/// <summary>
/// blur the image
/// </summary>
/// <param name="img">
/// image to manipulate
/// </param>
/// <param name="weight">
/// weight of effect
/// </param>
public static void Blur(ref ImageData img, double weight)
{
ConvolutionMatrix cMatrix = new ConvolutionMatrix(3);
cMatrix.SetAll(1);
cMatrix.Matrix[1, 1] = weight;
cMatrix.Factor = weight + 8;
ApplyConvolution3X3(ref img, cMatrix);
}
/// <summary>
/// find first occurence of color with tolerance
/// </summary>
/// <param name="img">
/// image to look in
/// </param>
/// <param name="searchColor">
/// color to look for
/// </param>
/// <param name="tolerance">
/// tolerance
/// </param>
/// <returns>
/// The <see cref="bool" /> 2dim array.
/// </returns>
public static bool[,] FindColors(ImageData img, Color searchColor, uint tolerance)
{
bool[,] grid = new bool[img.Width, img.Height];
for(int column = 0; column < img.Width; column++)
{
for(int row = 0; row < img.Height; row++)
{
if(ColorsSimilar(img.GetPixel(column, row), searchColor, tolerance))
{
grid[column, row] = true;
}
else
{
grid[column, row] = false;
}
}
}
return grid;
}
/// <summary>
/// get the red channel as array
/// </summary>
/// <param name="img">
/// image
/// </param>
/// <returns>
/// array[] of red channel
/// </returns>
public static uint[,] ExtractRedChannel(ImageData img)
{
uint[,] red = new uint[img.Width, img.Height];
for(int column = 0; column < img.Width; column++)
{
for(int row = 0; row < img.Height; row++)
{
Color c = img.GetPixel(column, row);
red[column, row] = c.R;
}
}
return red;
}
/// <summary>
/// Convert image to grayscale
/// </summary>
/// <param name="img">
/// ref image to convert
/// </param>
public static void Grayscale(ref ImageData img)
{
for(int column = 0; column < img.Width; column++)
{
for(int row = 0; row < img.Height; row++)
{
Color c = img[column, row];
int grayScale = (int)((c.R * .3) + (c.G * .59) + (c.B * .11));
img[column, row] = Color.FromArgb(grayScale, grayScale, grayScale);
}
}
}
/// <summary>
/// identify the color of a part(rectangle) from an image by a given list of reference colors
/// </summary>
/// <param name="img">
/// image to look in
/// </param>
/// <param name="statReference">
/// list of possible colors
/// </param>
/// <param name="left">
/// left of rectangle (default: 0)
/// </param>
/// <param name="top">
/// top of rectangle (default: 0)
/// </param>
/// <param name="width">
/// width of rectangle (default: full width)
/// </param>
/// <param name="height">
/// height of rectangle (default: full height)
/// </param>
/// <returns>
/// Color
/// </returns>
public static Color IdentifyColor(
ImageData img,
Dictionary<Color, List<double>> statReference,
int left = 0,
int top = 0,
int width = -1,
int height = -1)
{
double[] av = AverageRgbValues(img, left, top, width, height);
double bestScore = 255;
Color foo = Color.White;
foreach(KeyValuePair<Color, List<double>> item in statReference)
{
double currentScore = Math.Pow((item.Value[0] / 255.0) - (av[0] / 255.0), 2)
+ Math.Pow((item.Value[1] / 255.0) - (av[1] / 255.0), 2)
+ Math.Pow((item.Value[2] / 255.0) - (av[2] / 255.0), 2);
if(currentScore < bestScore)
{
foo = item.Key;
bestScore = currentScore;
}
}
return foo;
}
/// <summary>
/// invert image
/// </summary>
/// <param name="img">
/// ref image to convert
/// </param>
public static void Invert(ref ImageData img)
{
for(int column = 0; column < img.Width; column++)
{
for(int row = 0; row < img.Height; row++)
{
Color c = img[column, row];
img[column, row] = Color.FromArgb(255 - c.R, 255 - c.G, 255 - c.B);
}
}
}
/// <summary>
/// calculate the similarity of image A in a given rectangle and a reference image B
/// </summary>
/// <param name="img">
/// image A
/// </param>
/// <param name="reference">
/// image B
/// </param>
/// <param name="left">
/// offset from left of image A
/// </param>
/// <param name="top">
/// offset from top of image A
/// </param>
/// <param name="width">
/// width of rectangle (default: full width)
/// </param>
/// <param name="height">
/// height of rectangle (default: full height)
/// </param>
/// <param name="offsetLeft">
/// The Offset Left.
/// </param>
/// <param name="offsetTop">
/// The Offset Top.
/// </param>
/// <returns>
/// similarity (1=exact,0=none)
/// </returns>
public static double Similarity(
ImageData img,
ImageData reference,
int left = 0,
int top = 0,
int width = -1,
int height = -1,
int offsetLeft = 0,
int offsetTop = 0)
{
double sim = 0.0;
width = (width == -1) ? img.Width - left : width;
height = (height == -1) ? img.Height - top : height;
if((img.Width == reference.Width) && (img.Height == reference.Height))
{
for(int column = left; column < left + width; column++)
{
for(int row = top; row < top + height; row++)
{
Color a = img.GetPixel(offsetLeft + column, offsetTop + row);
Color b = reference.GetPixel(column, row);
int cr = Math.Abs(a.R - b.R);
int cg = Math.Abs(a.G - b.G);
int cb = Math.Abs(a.B - b.B);
sim += (cr + cg + cb) / 3.0;
}
}
sim /= 255.0;
sim /= img.Height * img.Width;
}
return 1 - sim;
}
/// <summary>
/// mark a point in image
/// </summary>
/// <param name="img">
/// ref image to mark
/// </param>
/// <param name="location">
/// where to set marker
/// </param>
/// <param name="markColor">
/// color of marker
/// </param>
/// <param name="size">
/// size of marker (square)
/// </param>
public static void MarkPoint(ref ImageData img, Point location, Color markColor, uint size = 5)
{
for(int i = Convert.ToInt32(location.X - size); i < location.X + size; i++)
{
for(int j = Convert.ToInt32(location.Y - size); j < location.Y + size; j++)
{
img[i, j] = markColor;
}
}
}
/// <summary>
/// replace color by another color
/// </summary>
/// <param name="img">
/// ref Image
/// </param>
/// <param name="searchColor">
/// color to look for
/// </param>
/// <param name="replaceColor">
/// color to replace with
/// </param>
/// <param name="tolerance">
/// tolerance of reference color (0,...,255)
/// </param>
public static void ReplaceSimilarColor(ref ImageData img, Color searchColor, Color replaceColor, uint tolerance)
{
for(int outerX = 0; outerX < img.Width; outerX++)
{
for(int outerY = 0; outerY < img.Height; outerY++)
{
Color a = img[outerX, outerY];
if(CommonFunctions.ColorsSimilar(a, searchColor, tolerance))
{
img[outerX, outerY] = replaceColor;
}
}
}
}
/// <summary>
/// search for binary patterns
/// </summary>
/// <param name="img">
/// image to look in
/// </param>
/// <param name="pattern">
/// pattern to look for
/// </param>
/// <param name="tolerance">
/// tolerance (0,...,255)
/// </param>
/// <returns>
/// The <see cref="Rectangle" />.
/// </returns>
public static Rectangle BinaryPattern(ImageData img, bool[,] pattern, uint tolerance = 0)
{
// simple
Point location = Point.Empty;
Color referenceColor = Color.Wheat;
bool first = true;
for(int outerColumn = 0; outerColumn < img.Width - pattern.GetLength(1); outerColumn++)
{
for(int outerRow = 0; outerRow < img.Height - pattern.GetLength(0); outerRow++)
{
for(int innerColumn = 0; innerColumn < pattern.GetLength(1); innerColumn++)
{
for(int innerRow = 0; innerRow < pattern.GetLength(0); innerRow++)
{
if(pattern[innerRow, innerColumn])
{
if(first)
{
referenceColor = img[outerColumn, outerRow];
first = false;
}
else
{
if(CommonFunctions.ColorsSimilar(
referenceColor,
img[outerColumn + innerColumn, outerRow + innerRow],
tolerance))
{
// ok
}
else
{
// schlecht passt nicht
innerColumn = pattern.GetLength(1) + 10;
first = true;
break;
}
}
}
else
{
if(first == false)
{
// darf nicht passen!
if(CommonFunctions.ColorsSimilar(
referenceColor,
img[outerColumn + innerColumn, outerRow + innerRow],
tolerance))
{
// schlecht passt
innerColumn = img.Width + 10;
innerRow = img.Height + 10;
first = true;
}
}
}
}
}
if(first == false)
{
// matched
location.X = outerColumn;
location.Y = outerRow;
return new Rectangle(location.X, location.Y, pattern.GetLength(1), pattern.GetLength(0));
}
}
}
return Rectangle.Empty;
}