private static void DetectLensDistortion(int image_width, int image_height,
calibrationDot[,] grid,
grid2D overlay_grid,
List<List<double>> lines,
ref polynomial curve,
ref calibrationDot centre_of_distortion,
ref List<List<double>> best_rectified_lines,
int grid_offset_x, int grid_offset_y,
double scale,
ref double minimum_error,
int random_seed)
{
double centre_of_distortion_search_radius = image_width / 100f; //80.0f;
centre_of_distortion = new calibrationDot();
curve = FitCurve(image_width, image_height,
grid, overlay_grid,
centre_of_distortion,
centre_of_distortion_search_radius,
grid_offset_x, grid_offset_y, lines,
ref minimum_error,
random_seed);
if (curve != null)
{
double rotation = 0;
best_rectified_lines =
RectifyLines(lines,
image_width, image_height,
curve,
centre_of_distortion,
rotation, scale);
}
}
/// <summary>
/// shows the perimeter of the ideal rectified grid
/// </summary>
/// <param name="filename">raw image filename</param>
/// <param name="overlay_grid">ideal rectified grid</param>
/// <param name="output_filename">filename to save as</param>
private static void ShowOverlayGridPerimeter(string filename,
grid2D overlay_grid,
string output_filename)
{
Bitmap bmp = (Bitmap)Bitmap.FromFile(filename);
byte[] img = new byte[bmp.Width * bmp.Height * 3];
BitmapArrayConversions.updatebitmap(bmp, img);
if (overlay_grid != null)
{
overlay_grid.perimeter.show(img, bmp.Width, bmp.Height, 255, 0, 0, 0);
}
Bitmap output_bmp = new Bitmap(bmp.Width, bmp.Height, System.Drawing.Imaging.PixelFormat.Format24bppRgb);
BitmapArrayConversions.updatebitmap_unsafe(img, output_bmp);
if (output_filename.ToLower().EndsWith("jpg"))
output_bmp.Save(output_filename, System.Drawing.Imaging.ImageFormat.Jpeg);
if (output_filename.ToLower().EndsWith("bmp"))
output_bmp.Save(output_filename, System.Drawing.Imaging.ImageFormat.Bmp);
}
private static void BestFit(int grid_tx, int grid_ty,
calibrationDot[,] grid,
grid2D overlay_grid,
ref double min_dist,
ref double min_dx, ref double min_dy,
ref int min_hits,
ref int grid_offset_x, ref int grid_offset_y)
{
for (int off_x = -1; off_x <= 1; off_x++)
{
for (int off_y = -1; off_y <= 1; off_y++)
{
int grid_x_offset = -grid_tx + off_x;
int grid_y_offset = -grid_ty + off_y;
int grid_x_offset_start = 0;
int grid_x_offset_end = 0;
if (grid_x_offset < 0)
{
grid_x_offset_start = -grid_x_offset;
grid_x_offset_end = 0;
}
else
{
grid_x_offset_start = 0;
grid_x_offset_end = grid_x_offset;
}
int grid_y_offset_start = 0;
int grid_y_offset_end = 0;
if (grid_y_offset < 0)
{
grid_y_offset_start = -grid_y_offset;
grid_y_offset_end = 0;
}
else
{
grid_y_offset_start = 0;
grid_y_offset_end = grid_y_offset;
}
double dx = 0;
double dy = 0;
double dist = 0;
int hits = 0;
for (int grid_x = grid_x_offset_start; grid_x < grid.GetLength(0) - grid_x_offset_end; grid_x++)
{
for (int grid_y = grid_y_offset_start; grid_y < grid.GetLength(1) - grid_y_offset_end; grid_y++)
{
if (grid[grid_x, grid_y] != null)
{
if ((grid_x + grid_x_offset < overlay_grid.line_intercepts.GetLength(0)) &&
(grid_y + grid_y_offset < overlay_grid.line_intercepts.GetLength(1)))
{
double intercept_x = overlay_grid.line_intercepts[grid_x + grid_x_offset, grid_y + grid_y_offset, 0];
double intercept_y = overlay_grid.line_intercepts[grid_x + grid_x_offset, grid_y + grid_y_offset, 1];
double dxx = grid[grid_x, grid_y].x - intercept_x;
double dyy = grid[grid_x, grid_y].y - intercept_y;
dx += dxx;
dy += dyy;
dist += Math.Abs(dxx) + Math.Abs(dyy);
hits++;
}
}
}
}
if (hits > 0)
{
dx /= hits;
dy /= hits;
//double dist = Math.Sqrt(dx * dx + dy * dy);
if (dist < min_dist)
{
min_dist = dist;
min_dx = dx;
min_dy = dy;
min_hits = hits;
grid_offset_x = grid_x_offset;
grid_offset_y = grid_y_offset;
}
}
}
}
}
/// <summary>
/// returns an ideally spaced grid over the actual detected spots
/// </summary>
/// <param name="grid"></param>
/// <returns></returns>
private static grid2D OverlayIdealGrid(calibrationDot[,] grid,
List<calibrationDot> corners,
ref int grid_offset_x, ref int grid_offset_y,
int random_seed)
{
grid2D overlay_grid = null;
int grid_tx = -1;
int grid_ty = -1;
int grid_bx = -1;
int grid_by = -1;
int offset_x = 0;
int offset_y = 0;
bool found = false;
int max_region_area = 0;
// try searching horizontally and vertically
// then pick the result with the greatest area
for (int test_orientation = 0; test_orientation < 2; test_orientation++)
{
bool temp_found = false;
int temp_grid_tx = -1;
int temp_grid_ty = -1;
int temp_grid_bx = -1;
int temp_grid_by = -1;
int temp_offset_x = 0;
int temp_offset_y = 0;
switch (test_orientation)
{
case 0:
{
while ((temp_offset_y < 5) && (!temp_found))
{
temp_offset_x = 0;
while ((temp_offset_x < 3) && (!temp_found))
{
temp_grid_tx = temp_offset_x;
temp_grid_ty = temp_offset_y;
temp_grid_bx = grid.GetLength(0) - 1 - temp_offset_x;
temp_grid_by = grid.GetLength(1) - 1 - temp_offset_y;
if ((temp_grid_bx < grid.GetLength(0)) &&
(temp_grid_tx < grid.GetLength(0)) &&
(temp_grid_by < grid.GetLength(1)) &&
(temp_grid_ty < grid.GetLength(1)) &&
(temp_grid_ty >= 0) &&
(temp_grid_by >= 0) &&
(temp_grid_tx >= 0) &&
(temp_grid_bx >= 0))
{
if ((grid[temp_grid_tx, temp_grid_ty] != null) &&
(grid[temp_grid_bx, temp_grid_ty] != null) &&
(grid[temp_grid_bx, temp_grid_by] != null) &&
(grid[temp_grid_tx, temp_grid_by] != null))
{
temp_found = true;
}
}
temp_offset_x++;
}
temp_offset_y++;
}
break;
}
case 1:
{
while ((temp_offset_x < 3) && (!temp_found))
{
temp_offset_y = 0;
while ((temp_offset_y < 5) && (!temp_found))
{
temp_grid_tx = temp_offset_x;
temp_grid_ty = temp_offset_y;
temp_grid_bx = grid.GetLength(0) - 1 - temp_offset_x;
temp_grid_by = grid.GetLength(1) - 1 - temp_offset_y;
if ((temp_grid_bx < grid.GetLength(0)) &&
(temp_grid_tx < grid.GetLength(0)) &&
(temp_grid_by < grid.GetLength(1)) &&
(temp_grid_ty < grid.GetLength(1)) &&
(temp_grid_ty >= 0) &&
(temp_grid_by >= 0) &&
(temp_grid_tx >= 0) &&
(temp_grid_bx >= 0))
{
if ((grid[temp_grid_tx, temp_grid_ty] != null) &&
(grid[temp_grid_bx, temp_grid_ty] != null) &&
(grid[temp_grid_bx, temp_grid_by] != null) &&
(grid[temp_grid_tx, temp_grid_by] != null))
{
temp_found = true;
}
}
temp_offset_y++;
}
temp_offset_x++;
}
break;
}
}
temp_offset_y = temp_grid_ty - 1;
while (temp_offset_y >= 0)
{
if ((temp_offset_y < grid.GetLength(1)) &&
(temp_offset_y >= 0))
{
if ((grid[temp_grid_tx, temp_offset_y] != null) &&
(grid[temp_grid_bx, temp_offset_y] != null))
{
temp_grid_ty = temp_offset_y;
temp_offset_y--;
}
else break;
}
else break;
}
temp_offset_y = temp_grid_by + 1;
while (temp_offset_y < grid.GetLength(1))
{
if ((temp_offset_y < grid.GetLength(1)) &&
(temp_offset_y >= 0))
{
if ((grid[temp_grid_tx, temp_offset_y] != null) &&
(grid[temp_grid_bx, temp_offset_y] != null))
{
temp_grid_by = temp_offset_y;
temp_offset_y++;
}
else break;
}
else break;
}
if (temp_found)
{
int region_area = (temp_grid_bx - temp_grid_tx) * (temp_grid_by - temp_grid_ty);
if (region_area > max_region_area)
{
max_region_area = region_area;
found = true;
grid_tx = temp_grid_tx;
grid_ty = temp_grid_ty;
grid_bx = temp_grid_bx;
grid_by = temp_grid_by;
offset_x = temp_offset_x;
offset_y = temp_offset_y;
}
}
}
if (found)
{
// record the positions of the corners
corners.Add(grid[grid_tx, grid_ty]);
corners.Add(grid[grid_bx, grid_ty]);
corners.Add(grid[grid_bx, grid_by]);
corners.Add(grid[grid_tx, grid_by]);
double dx, dy;
double x0 = grid[grid_tx, grid_ty].x;
double y0 = grid[grid_tx, grid_ty].y;
double x1 = grid[grid_bx, grid_ty].x;
double y1 = grid[grid_bx, grid_ty].y;
double x2 = grid[grid_tx, grid_by].x;
double y2 = grid[grid_tx, grid_by].y;
double x3 = grid[grid_bx, grid_by].x;
double y3 = grid[grid_bx, grid_by].y;
polygon2D perimeter = new polygon2D();
perimeter.Add((float)x0, (float)y0);
perimeter.Add((float)x1, (float)y1);
perimeter.Add((float)x3, (float)y3);
perimeter.Add((float)x2, (float)y2);
int grid_width = grid_bx - grid_tx;
int grid_height = grid_by - grid_ty;
int min_hits = 0;
double min_dx = 0, min_dy = 0;
// try various perimeter sizes
double min_dist = double.MaxValue;
int max_perim_size_tries = 100;
polygon2D best_perimeter = perimeter;
MersenneTwister rnd = new MersenneTwister(random_seed);
for (int perim_size = 0; perim_size < max_perim_size_tries; perim_size++)
{
// try a small range of translations
for (int nudge_x = -10; nudge_x <= 10; nudge_x++)
{
for (int nudge_y = -5; nudge_y <= 5; nudge_y++)
{
// create a perimeter at this scale and translation
polygon2D temp_perimeter = perimeter.Scale(1.0f + (perim_size * 0.1f / max_perim_size_tries));
temp_perimeter = temp_perimeter.ScaleSideLength(0, 0.95f + ((float)rnd.NextDouble() * 0.1f));
temp_perimeter = temp_perimeter.ScaleSideLength(2, 0.95f + ((float)rnd.NextDouble() * 0.1f));
for (int i = 0; i < temp_perimeter.x_points.Count; i++)
{
temp_perimeter.x_points[i] += nudge_x;
temp_perimeter.y_points[i] += nudge_y;
}
// create a grid based upon the perimeter
grid2D temp_overlay_grid = new grid2D(grid_width, grid_height, temp_perimeter, 0, false);
// how closely does the grid fit the actual observations ?
double temp_min_dist = min_dist;
BestFit(grid_tx, grid_ty, grid,
temp_overlay_grid, ref min_dist,
ref min_dx, ref min_dy, ref min_hits,
ref grid_offset_x, ref grid_offset_y);
// record the closest fit
if (temp_min_dist < min_dist)
{
best_perimeter = temp_perimeter;
overlay_grid = temp_overlay_grid;
}
}
}
}
if (min_hits > 0)
{
dx = min_dx;
dy = min_dy;
Console.WriteLine("dx: " + dx.ToString());
Console.WriteLine("dy: " + dy.ToString());
x0 += dx;
y0 += dy;
x1 += dx;
y1 += dy;
x2 += dx;
y2 += dy;
x3 += dx;
y3 += dy;
perimeter = new polygon2D();
perimeter.Add((float)x0, (float)y0);
perimeter.Add((float)x1, (float)y1);
perimeter.Add((float)x3, (float)y3);
perimeter.Add((float)x2, (float)y2);
overlay_grid = new grid2D(grid_width, grid_height, perimeter, 0, false);
}
}
return (overlay_grid);
}
/// <summary>
/// fits a curve to the given grid using the given centre of distortion
/// </summary>
/// <param name="grid">detected grid dots</param>
/// <param name="overlay_grid">overlayed ideal rectified grid</param>
/// <param name="centre_of_distortion">centre of lens distortion</param>
/// <param name="curve">curve to be fitted</param>
private static void FitCurve(calibrationDot[,] grid,
grid2D overlay_grid,
calibrationDot centre_of_distortion,
polynomial curve,
double noise, MersenneTwister rnd,
int grid_offset_x, int grid_offset_y)
{
double[] prev_col = new double[grid.GetLength(1) * 2];
double[] col = new double[prev_col.Length];
double half_noise = noise / 2;
double rectified_x, rectified_y;
for (int pass = 0; pass < 1; pass++)
{
// for every detected dot
for (int grid_x = 0; grid_x < grid.GetLength(0); grid_x++)
{
double prev_rectified_radial_dist = 0;
double prev_actual_radial_dist = 0;
int prev_grid_y = -1;
for (int grid_y = 0; grid_y < grid.GetLength(1); grid_y++)
{
if (grid[grid_x, grid_y] != null)
{
if ((grid_x + grid_offset_x < overlay_grid.line_intercepts.GetLength(0)) &&
(grid_y + grid_offset_y < overlay_grid.line_intercepts.GetLength(1)) &&
(grid_x + grid_offset_x >= 0) && (grid_y + grid_offset_y >= 0))
{
// find the rectified distance of the dot from the centre of distortion
rectified_x = overlay_grid.line_intercepts[grid_x + grid_offset_x, grid_y + grid_offset_y, 0];
rectified_y = overlay_grid.line_intercepts[grid_x + grid_offset_x, grid_y + grid_offset_y, 1];
if (pass > 0)
{
rectified_x += (((rnd.NextDouble() * noise) - half_noise) * 0.1);
rectified_y += (((rnd.NextDouble() * noise) - half_noise) * 0.1);
}
//double rectified_x = overlay_grid.line_intercepts[grid_x + grid_offset_x, grid_y + grid_offset_y, 0];
//double rectified_y = overlay_grid.line_intercepts[grid_x + grid_offset_x, grid_y + grid_offset_y, 1];
double rectified_dx = rectified_x - centre_of_distortion.x;
double rectified_dy = rectified_y - centre_of_distortion.y;
double rectified_radial_dist = Math.Sqrt(rectified_dx * rectified_dx + rectified_dy * rectified_dy);
// find the actual raw image distance of the dot from the centre of distortion
//double actual_x = grid[grid_x, grid_y].x + (((rnd.NextDouble() * noise) - half_noise) * 2);
//double actual_y = grid[grid_x, grid_y].y + (((rnd.NextDouble() * noise) - half_noise) * 2);
double actual_x = grid[grid_x, grid_y].x;
double actual_y = grid[grid_x, grid_y].y;
double actual_dx = actual_x - centre_of_distortion.x;
double actual_dy = actual_y - centre_of_distortion.y;
double actual_radial_dist = Math.Sqrt(actual_dx * actual_dx + actual_dy * actual_dy);
// plot
curve.AddPoint(rectified_radial_dist, actual_radial_dist);
col[(grid_y * 2)] = rectified_radial_dist;
col[(grid_y * 2) + 1] = actual_radial_dist;
prev_rectified_radial_dist = rectified_radial_dist;
prev_actual_radial_dist = actual_radial_dist;
prev_grid_y = grid_y;
}
}
}
for (int i = 0; i < col.Length; i++)
prev_col[i] = col[i];
}
}
// find the best fit curve
curve.Solve();
}
/// <summary>
/// fits a curve to the given grid using the given centre of distortion
/// </summary>
/// <param name="image_width">width of the image in pixels</param>
/// <param name="image_height">height of the image in pixels</param>
/// <param name="grid">detected grid dots</param>
/// <param name="overlay_grid">overlayed ideal rectified grid</param>
/// <param name="centre_of_distortion">centre of lens distortion</param>
/// <param name="centre_of_distortion_search_radius">search radius for the centre of distortion</param>
/// <returns>fitted curve</returns>
private static polynomial FitCurve(int image_width, int image_height,
calibrationDot[,] grid,
grid2D overlay_grid,
calibrationDot centre_of_distortion,
double centre_of_distortion_search_radius,
int grid_offset_x, int grid_offset_y,
List<List<double>> lines,
ref double minimum_error,
int random_seed)
{
double overall_minimum_error = double.MaxValue;
double centre_of_distortion_x=0, centre_of_distortion_y=0;
polynomial overall_best_curve = null;
polynomial best_curve = null;
for (int rand_pass = random_seed; rand_pass < random_seed + 3; rand_pass++)
{
minimum_error = double.MaxValue;
double search_min_error = minimum_error;
int degrees = 3;
int best_degrees = degrees;
List<double> prev_minimum_error = new List<double>();
prev_minimum_error.Add(minimum_error);
double increment = 3.0f;
double noise = increment / 2;
best_curve = null;
double search_radius = (float)centre_of_distortion_search_radius;
double half_width = image_width / 2;
double half_height = image_height / 2;
double half_noise = noise / 2;
double max_radius_sqr = centre_of_distortion_search_radius * centre_of_distortion_search_radius;
int scaled_up = 0;
List<double> result = new List<double>();
double best_cx = half_width, best_cy = half_height;
float maxerr = (image_width / 2) * (image_width / 2);
MersenneTwister rnd = new MersenneTwister(rand_pass);
int max_passes = 1000;
for (int pass = 0; pass < max_passes; pass++)
{
double centre_x = 0;
double centre_y = 0;
double mass = 0;
for (double cx = half_width - search_radius; cx < half_width + search_radius; cx += increment)
{
double dx = cx - half_width;
for (double cy = half_height - search_radius; cy < half_height + search_radius; cy += increment)
{
double dy = cy - half_height;
double dist = dx * dx + dy * dy;
if (dist < max_radius_sqr)
{
polynomial curve = new polynomial();
curve.SetDegree(degrees);
centre_of_distortion.x = cx + (rnd.NextDouble() * noise) - half_noise;
centre_of_distortion.y = cy + (rnd.NextDouble() * noise) - half_noise;
FitCurve(grid, overlay_grid, centre_of_distortion, curve, noise, rnd, grid_offset_x, grid_offset_y);
// do a sanity check on the curve
if (ValidCurve(curve, image_width))
{
double error = curve.GetMeanError();
error = error * error;
if (error > 0.001)
{
error = maxerr - error; // inverse
if (error > 0)
{
centre_x += centre_of_distortion.x * error;
centre_y += centre_of_distortion.y * error;
mass += error;
}
}
}
}
}
}
if (mass > 0)
{
centre_x /= mass;
centre_y /= mass;
centre_of_distortion.x = centre_x;
centre_of_distortion.y = centre_y;
polynomial curve2 = new polynomial();
curve2.SetDegree(degrees);
FitCurve(grid, overlay_grid, centre_of_distortion, curve2, noise, rnd, grid_offset_x, grid_offset_y);
double mean_error = curve2.GetMeanError();
double scaledown = 0.99999999999999999;
if (mean_error < search_min_error)
{
search_min_error = mean_error;
// cool down
prev_minimum_error.Add(search_min_error);
search_radius *= scaledown;
increment *= scaledown;
noise = increment / 2;
half_noise = noise / 2;
half_width = centre_x;
half_height = centre_y;
if (mean_error < minimum_error)
{
best_cx = half_width;
best_cy = half_height;
minimum_error = mean_error;
Console.WriteLine("Cool " + pass.ToString() + ": " + mean_error.ToString());
if (max_passes - pass < 500) max_passes += 500;
best_degrees = degrees;
best_curve = curve2;
}
scaled_up = 0;
}
else
{
// heat up
double scaleup = 1.0 / scaledown;
search_radius /= scaledown;
increment /= scaledown;
noise = increment / 2;
half_noise = noise / 2;
scaled_up++;
half_width = best_cx + (rnd.NextDouble() * noise) - half_noise;
half_height = best_cy + (rnd.NextDouble() * noise) - half_noise;
if (prev_minimum_error.Count > 0)
{
minimum_error = prev_minimum_error[prev_minimum_error.Count - 1];
prev_minimum_error.RemoveAt(prev_minimum_error.Count - 1);
}
}
result.Add(mean_error);
}
}
minimum_error = Math.Sqrt(minimum_error);
centre_of_distortion.x = best_cx;
centre_of_distortion.y = best_cy;
if (best_curve != null)
minimum_error = best_curve.GetMeanError();
if (minimum_error < overall_minimum_error)
{
overall_minimum_error = minimum_error;
centre_of_distortion_x = best_cx;
centre_of_distortion_y = best_cy;
overall_best_curve = best_curve;
}
}
overall_minimum_error = minimum_error;
centre_of_distortion.x = centre_of_distortion_x;
centre_of_distortion.y = centre_of_distortion_y;
best_curve = overall_best_curve;
return (best_curve);
}
/// <summary>
/// detect a grid within the given image using the given perimeter polygon
/// </summary>
/// <param name="img">image data</param>
/// <param name="img_width">width of the image</param>
/// <param name="img_height">height of the image</param>
/// <param name="bytes_per_pixel">number of bytes per pixel</param>
/// <param name="perimeter">bounding perimeter within which the grid exists</param>
/// <param name="spot_centres">previously detected spot centres</param>
/// <param name="minimum_dimension_horizontal">minimum number of cells across</param>
/// <param name="maximum_dimension_horizontal">maximum number of cells across</param>
/// <param name="minimum_dimension_vertical">minimum number of cells down</param>
/// <param name="maximum_dimension_vertical">maximum number of cells down</param>
/// <param name="known_grid_spacing">known grid spacing (cell diameter) value in pixels</param>
/// <param name="known_even_dimension">set to true if it is known that the number of cells in horizontal and vertical axes is even</param>
/// <param name="border_cells">extra cells to add as a buffer zone around the grid</param>
/// <param name="horizontal_scale_spacings">description used on the spacings diagram</param>
/// <param name="vertical_scale_spacings">description used on the spacings diagram</param>
/// <param name="average_spacing_horizontal"></param>
/// <param name="average_spacing_vertical"></param>
/// <param name="output_img"></param>
/// <param name="output_img_width"></param>
/// <param name="output_img_height"></param>
/// <param name="output_img_type"></param>
/// <param name="ideal_grid_colour">colour used to draw the ideal grid</param>
/// <param name="detected_grid_colour">colour used to draw the detected grid</param>
/// <param name="simple_orientation"></param>
/// <returns>2D grid</returns>
public static grid2D DetectGrid(byte[] img, int img_width, int img_height, int bytes_per_pixel,
polygon2D perimeter, ArrayList spot_centres,
int minimum_dimension_horizontal, int maximum_dimension_horizontal,
int minimum_dimension_vertical, int maximum_dimension_vertical,
float known_grid_spacing, bool known_even_dimension,
int border_cells,
String horizontal_scale_spacings, String vertical_scale_spacings,
ref float average_spacing_horizontal,
ref float average_spacing_vertical,
ref byte[] output_img, int output_img_width, int output_img_height,
int output_img_type,
byte[] ideal_grid_colour, byte[] detected_grid_colour,
bool simple_orientation)
{
int tx = (int)perimeter.left();
int ty = (int)perimeter.top();
int bx = (int)perimeter.right();
int by = (int)perimeter.bottom();
// adjust spot centre positions so that they're relative to the perimeter
// top left position
if (spot_centres != null)
{
for (int i = 0; i < spot_centres.Count; i += 2)
{
spot_centres[i] = (float)spot_centres[i] - tx;
spot_centres[i + 1] = (float)spot_centres[i + 1] - ty;
}
}
int wdth = bx - tx;
int hght = by - ty;
// create an image of the grid area
byte[] grid_img = image.createSubImage(img, img_width, img_height, bytes_per_pixel,
tx, ty, bx, by);
// get the orientation of the perimeter
float dominant_orientation = perimeter.GetSquareOrientation();
// find the horizontal and vertical dimensions of the grid perimeter
float grid_horizontal = perimeter.GetSquareHorizontal();
float grid_vertical = perimeter.GetSquareVertical();
// detect grid within the perimeter
int cells_horizontal = 0, cells_vertical = 0;
float horizontal_phase_offset = 0;
float vertical_phase_offset = 0;
if (spot_centres == null)
DetectGrid(grid_img, wdth, hght, bytes_per_pixel,
dominant_orientation, known_grid_spacing,
grid_horizontal, grid_vertical,
minimum_dimension_horizontal, maximum_dimension_horizontal,
minimum_dimension_vertical, maximum_dimension_vertical,
horizontal_scale_spacings, vertical_scale_spacings,
ref average_spacing_horizontal, ref average_spacing_vertical,
ref horizontal_phase_offset, ref vertical_phase_offset,
ref cells_horizontal, ref cells_vertical,
ref output_img, output_img_width, output_img_height, output_img_type,
ideal_grid_colour, detected_grid_colour);
else
DetectGrid(spot_centres, grid_img, wdth, hght, bytes_per_pixel,
dominant_orientation, known_grid_spacing,
grid_horizontal, grid_vertical,
minimum_dimension_horizontal, maximum_dimension_horizontal,
minimum_dimension_vertical, maximum_dimension_vertical,
horizontal_scale_spacings, vertical_scale_spacings,
ref average_spacing_horizontal, ref average_spacing_vertical,
ref horizontal_phase_offset, ref vertical_phase_offset,
ref cells_horizontal, ref cells_vertical,
ref output_img, output_img_width, output_img_height, output_img_type,
ideal_grid_colour, detected_grid_colour);
grid2D detectedGrid = null;
// apply some range limits
bool range_limited = false;
if (cells_horizontal < 3)
{
cells_horizontal = 3;
range_limited = true;
}
if (cells_vertical < 3)
{
cells_vertical = 3;
range_limited = true;
}
if (cells_horizontal > maximum_dimension_horizontal)
{
cells_horizontal = maximum_dimension_horizontal;
range_limited = true;
}
if (cells_vertical > maximum_dimension_vertical)
{
cells_vertical = maximum_dimension_vertical;
range_limited = true;
}
if (range_limited)
{
Console.WriteLine("WARNING: When detecting the grid the matrix dimension had to be artificially restricted.");
Console.WriteLine(" This probably means that there is a problem with the original image");
}
// if we know the number of cells should be even correct any inaccuracies
if (known_even_dimension)
{
cells_horizontal = (int)(cells_horizontal / 2) * 2;
cells_vertical = (int)(cells_vertical / 2) * 2;
}
// get the centre of the region
float cx = tx + ((bx - tx) / 2);
float cy = ty + ((by - ty) / 2);
detectedGrid = new grid2D(cells_horizontal, cells_vertical,
cx, cy, dominant_orientation,
average_spacing_horizontal, average_spacing_vertical,
horizontal_phase_offset, vertical_phase_offset,
border_cells, simple_orientation);
return (detectedGrid);
}
/// <summary>
/// simple function used to test grid creation
/// </summary>
/// <param name="filename">filename of the test image to be created</param>
public static void Test(string filename)
{
int image_width = 640;
int image_height = 480;
int dimension_x = 10;
int dimension_y = 10;
Bitmap bmp = new Bitmap(image_width, image_height, System.Drawing.Imaging.PixelFormat.Format24bppRgb);
byte[] img = new byte[image_width * image_height * 3];
polygon2D test_poly;
grid2D grid;
test_poly = new polygon2D();
test_poly.Add(image_width * 15 / 100, image_height * 20 / 100);
test_poly.Add(image_width * 40 / 100, image_height * 20 / 100);
test_poly.Add(image_width * 40 / 100, image_height * 40 / 100);
test_poly.Add(image_width * 15 / 100, image_height * 40 / 100);
grid = new grid2D(dimension_x, dimension_y, test_poly, 0, false);
grid.ShowLines(img, image_width, image_height, 0, 255, 0, 0);
int half_width = image_width / 2;
test_poly = new polygon2D();
test_poly.Add(half_width + (image_width * 20 / 100), image_height * 20 / 100);
test_poly.Add(half_width + (image_width * 35 / 100), image_height * 20 / 100);
test_poly.Add(half_width + (image_width * 40 / 100), image_height * 40 / 100);
test_poly.Add(half_width + (image_width * 15 / 100), image_height * 40 / 100);
grid = new grid2D(dimension_x, dimension_y, test_poly, 0, false);
grid.ShowLines(img, image_width, image_height, 0, 255, 0, 0);
int half_height = image_height / 2;
test_poly = new polygon2D();
test_poly.Add(image_width * 15 / 100, half_height + (image_height * 24 / 100));
test_poly.Add(image_width * 40 / 100, half_height + (image_height * 20 / 100));
test_poly.Add(image_width * 40 / 100, half_height + (image_height * 40 / 100));
test_poly.Add(image_width * 15 / 100, half_height + (image_height * 36 / 100));
grid = new grid2D(dimension_x, dimension_y, test_poly, 0, false);
grid.ShowLines(img, image_width, image_height, 0, 255, 0, 0);
test_poly = new polygon2D();
test_poly.Add(half_width + (image_width * 20 / 100), half_height + (image_height * 24 / 100));
test_poly.Add(half_width + (image_width * 35 / 100), half_height + (image_height * 20 / 100));
test_poly.Add(half_width + (image_width * 40 / 100), half_height + (image_height * 40 / 100));
test_poly.Add(half_width + (image_width * 15 / 100), half_height + (image_height * 36 / 100));
grid = new grid2D(dimension_x, dimension_y, test_poly, 0, false);
grid.ShowLines(img, image_width, image_height, 0, 255, 0, 0);
BitmapArrayConversions.updatebitmap_unsafe(img, bmp);
bmp.Save(filename);
}
/// <summary>
/// rescales the grid to a larger or smaller image
/// </summary>
/// <param name="original_image_width"></param>
/// <param name="original_image_height"></param>
/// <param name="new_image_width"></param>
/// <param name="new_image_height"></param>
/// <returns></returns>
public grid2D Scale(int original_image_width, int original_image_height,
int new_image_width, int new_image_height)
{
polygon2D new_perimeter = perimeter.Copy();
for (int i = 0; i < new_perimeter.x_points.Count; i++)
{
float x = (float)new_perimeter.x_points[i] * new_image_width / original_image_width;
float y = (float)new_perimeter.y_points[i] * new_image_height / original_image_height;
new_perimeter.x_points[i] = x;
new_perimeter.y_points[i] = y;
}
grid2D new_grid = new grid2D(cell.Length, cell[0].Length);
new_grid.init(cell.Length, cell[0].Length,
new_perimeter, 0, false);
return (new_grid);
}