/// <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);
}
/// <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 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>
/// 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;
Random rnd = new Random(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);
}
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>
/// 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, Random 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);
Random rnd = new Random(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>
/// 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);
}
/// <summary>
/// returns an ideal grid with perfectly regular spacing
/// </summary>
/// <param name="grid"></param>
/// <param name="image_width"></param>
/// <param name="image_height"></param>
/// <returns>
/// </returns>
private static grid2D GetIdealGrid(CalibrationDot[,] grid,
int image_width, int image_height)
{
grid2D ideal_grid = null;
float ideal_spacing = 0;
double centre_x = image_width / 2;
double centre_y = image_height / 2;
double min_dist = double.MaxValue;
int grid_cx=0, grid_cy=0;
for (int x = 0; x < grid.GetLength(0); x++)
{
for (int y = 0; y < grid.GetLength(1); y++)
{
if (grid[x, y] != null)
{
double dx = grid[x, y].x - centre_x;
double dy = grid[x, y].y - centre_y;
double dist = dx*dx + dy*dy;
if (dist < min_dist)
{
min_dist = dist;
grid_cx = x;
grid_cy = y;
}
}
}
}
if (grid_cx > 0)
{
int[] orientation_histogram = new int[361];
List<double>[] orientations = new List<double>[361];
double average_dist = 0;
int hits = 0;
int local_search = 2;
for (int x = grid_cx - local_search; x <= grid_cx + local_search; x++)
{
if ((x >= 0) && (x < grid.GetLength(0)-1))
{
for (int y = grid_cy - local_search; y <= grid_cy + local_search; y++)
{
if ((y >= 1) && (y < grid.GetLength(1)-1))
{
if (grid[x, y] != null)
{
for (int i = 0; i < grid[x, y].Links.Count; i++)
{
CalibrationLink link = (CalibrationLink)grid[x, y].Links[i];
CalibrationDot from_dot = (CalibrationDot)link.From;
double dx = grid[x, y].x - from_dot.x;
double dy = grid[x, y].y - from_dot.y;
double dist = Math.Sqrt(dx*dx + dy*dy);
if (dist > 0)
{
double orientation = Math.Asin(dx / dist);
if (orientation < 0) orientation += Math.PI;
if (dy < 0) orientation = (Math.PI * 2) - orientation;
orientation = orientation / Math.PI * 180;
int bucket = (int)orientation;
orientation_histogram[bucket]++;
if (orientations[bucket] == null) orientations[bucket] = new List<double>();
orientations[bucket].Add(orientation);
average_dist += Math.Sqrt(dx*dx + dy*dy);
hits++;
}
}
}
}
}
}
}
if (hits > 0) average_dist = average_dist / hits;
ideal_spacing = (float)average_dist;
int max_orientation_response = 0;
int best_ang = 0;
for (int ang = 0; ang < 90; ang++)
{
int response = orientation_histogram[ang] +
orientation_histogram[ang + 90] +
orientation_histogram[ang + 180];
if (response > max_orientation_response)
{
max_orientation_response = response;
best_ang = ang;
}
}
double average_orientation = 0;
hits = 0;
for (int offset = 0; offset < 3; offset++)
{
if (orientations[best_ang + offset] != null)
{
for (int ang = 0; ang < orientations[best_ang + offset].Count; ang++)
{
average_orientation += orientations[best_ang + offset][ang] - (Math.PI*offset/2);
hits++;
}
}
}
if (hits > 0)
{
average_orientation /= hits;
float pattern_orientation = (float)average_orientation;
float offset_x = (float)grid[grid_cx, grid_cy].x;
float offset_y = (float)grid[grid_cx, grid_cy].y;
float r = ideal_spacing * dots_across;
polygon2D perimeter = new polygon2D();
perimeter.Add(-r + offset_x, -r + offset_y);
perimeter.Add(r + offset_x, -r + offset_y);
perimeter.Add(r + offset_x, r + offset_y);
perimeter.Add(-r + offset_x, r + offset_y);
perimeter.rotate((float)average_orientation / 180 * (float)Math.PI, offset_x, offset_y);
ideal_grid = new grid2D(dots_across*2, dots_across*2, perimeter, 0, false);
int grid_width = grid.GetLength(0);
int grid_height = grid.GetLength(1);
int idx = 0;
int xx=0, yy=0;
float ideal_x, ideal_y;
for (int orient = 0; orient < 8; orient++)
{
for (int x = 0; x < grid_width; x++)
{
for (int y = 0; y < grid_height; y++)
{
if (grid[x, y] != null)
{
switch(orient)
{
case 0:
{
xx = (x - grid_cx) + dots_across;
yy = (y - grid_cy) + dots_across;
break;
}
case 1:
{
xx = (x - grid_cx) + dots_across;
yy = (grid_cy - y) + dots_across;
break;
}
case 2:
{
xx = (grid_cx - x) + dots_across;
yy = (y - grid_cy) + dots_across;
break;
}
case 3:
{
xx = (grid_cx - x) + dots_across;
yy = (grid_cy - y) + dots_across;
break;
}
case 4:
{
xx = (y - grid_cy) + dots_across;
yy = (x - grid_cx) + dots_across;
break;
}
case 5:
{
xx = (y - grid_cy) + dots_across;
yy = (grid_cx - x) + dots_across;
break;
}
case 6:
{
xx = (grid_cy - y) + dots_across;
yy = (x - grid_cx) + dots_across;
break;
}
case 7:
{
xx = (grid_cy - y) + dots_across;
yy = (grid_cx - x) + dots_across;
break;
}
}
if ((xx >= 0) && (xx < ideal_grid.cell.Length) &&
(yy >= 0) && (yy < ideal_grid.cell[0].Length))
{
ideal_x = ideal_grid.cell[xx][yy].perimeter.x_points[idx];
ideal_y = ideal_grid.cell[xx][yy].perimeter.y_points[idx];
if (orient == 0)
{
grid[x, y].rectified_x = ideal_x;
grid[x, y].rectified_y = ideal_y;
}
else
{
double diff_x1 = grid[x, y].rectified_x - grid[x, y].x;
double diff_y1 = grid[x, y].rectified_y - grid[x, y].y;
double dist1 = diff_x1*diff_x1 + diff_y1*diff_y1;
double diff_x2 = ideal_x - grid[x, y].x;
double diff_y2 = ideal_y - grid[x, y].y;
double dist2 = diff_x2*diff_x2 + diff_y2*diff_y2;
if (dist2 < dist1)
{
grid[x, y].rectified_x = ideal_x;
grid[x, y].rectified_y = ideal_y;
}
}
}
}
}
}
}
}
}
return(ideal_grid);
}
private static void ShowIdealGrid(Bitmap bmp,
grid2D ideal_grid,
CalibrationDot[,] grid,
ref Bitmap output_bmp)
{
byte[] img = new byte[bmp.Width * bmp.Height * 3];
BitmapArrayConversions.updatebitmap(bmp, img);
if (grid != null)
{
for (int grid_x = 0; grid_x < grid.GetLength(0); grid_x++)
{
for (int grid_y = 0; grid_y < grid.GetLength(1); grid_y++)
{
if (grid[grid_x, grid_y] != null)
{
drawing.drawCross(img, bmp.Width, bmp.Height,
(int)grid[grid_x, grid_y].x, (int)grid[grid_x, grid_y].y,
1, 0,255,0,0);
}
}
}
}
if (ideal_grid != null) ideal_grid.ShowIntercepts(img, bmp.Width, bmp.Height, 255,0,0, 3, 0);
if (output_bmp == null)
output_bmp = new Bitmap(bmp.Width, bmp.Height, System.Drawing.Imaging.PixelFormat.Format24bppRgb);
BitmapArrayConversions.updatebitmap_unsafe(img, output_bmp);
}