public myPicture doSmooth(myPicture input, matrix mat)
{
Bitmap ret = new Bitmap(input.width, input.height);
int r = mat.n / 2, s = mat.m / 2;
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
double tmp = 0;
for (int p = -r; p <= r; ++p)
{
for (int q = -s; q <= s; ++q)
{
tmp += 1.0 * input.getGrayDegree(i - p, j - q) * mat.a[p + r, q + s];
}
}
int val = (int)tmp;
if (val < 0)
{
val = 0;
}
if (val > 255)
{
val = 255;
}
ret.SetPixel(i, j, Color.FromArgb(val, val, val));
}
}
return(new myPicture(ret, input.path));
}
public myPicture doSharp(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
int dx = (input.getGrayDegree(i - 1, j - 1) + 2 * input.getGrayDegree(i - 1, j) + input.getGrayDegree(i - 1, j + 1)) - (input.getGrayDegree(i + 1, j - 1) + 2 * input.getGrayDegree(i + 1, j) + input.getGrayDegree(i + 1, j + 1));
int dy = (input.getGrayDegree(i - 1, j + 1) + 2 * input.getGrayDegree(i, j + 1) + input.getGrayDegree(i + 1, j + 1)) - (input.getGrayDegree(i - 1, j - 1) + 2 * input.getGrayDegree(i, j - 1) + input.getGrayDegree(i + 1, j - 1));
if (dx < 0)
{
dx = -dx;
}
if (dy < 0)
{
dy = -dy;
}
int d = Math.Max(dx, dy);
if (d > 255)
{
d = 255;
}
ret.SetPixel(i, j, Color.FromArgb(d, d, d));
}
}
return(new myPicture(ret, input.path));
}
//输入：原图
public getDigits(myPicture input)
{
int width = input.width;
int height = input.height;
//生成图片
Bitmap pic = new Bitmap(width, height);
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
int cur = input.grayDegree[i, j];
pic.SetPixel(i, j, Color.FromArgb(cur, cur, cur));
}
}
//获取文件路径和文件格式
int len = input.path.Length, pos = -1;
for (int i = len - 1; i >= 0; i--)
{
if (input.path[i] == '.')
{
pos = i;
}
}
if (pos != -1)
{
filePath = input.path.Substring(0, pos) + "_gray.bmp";
}
else
{
filePath = input.path + ".bmp";
}
System.Drawing.Imaging.ImageFormat imgformat = System.Drawing.Imaging.ImageFormat.Bmp;
//保存图片
pic.Save(filePath, imgformat);
//调用第三方软件
Process myPro = new Process();
myPro.StartInfo.FileName = "cmd.exe";
myPro.StartInfo.UseShellExecute = false;
myPro.StartInfo.RedirectStandardInput = true;
myPro.StartInfo.RedirectStandardOutput = true;
myPro.StartInfo.RedirectStandardError = true;
myPro.StartInfo.CreateNoWindow = true;
myPro.Start();
textPath = filePath.Substring(0, filePath.Length - 4);
string str = "tesseract " + filePath + " " + textPath + " digits";
myPro.StandardInput.WriteLine(str);
myPro.StandardInput.AutoFlush = true;
myPro.Close();
}
//输入：锐化和二值化后的图像，输出：找到的最大连通块，即最外层圆
public myPicture init(myPicture input)
{
width = input.width;
height = input.height;
gray = new int[width, height];
vis = new int[width, height];
//获取灰度值
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
gray[i, j] = input.picture.GetPixel(i, j).B;
vis[i, j] = 0;
}
}
//找到最大连通块
int cou = 0, no = 1, ans = 0;
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
if (vis[i, j] == 0 && gray[i, j] == 255)
{
cnt = 0;
dfs(i, j, no);
if (cou < cnt)
{
cou = cnt;
ans = no;
}
no++;
}
}
}
//将最大连通块变为白色，其他区域变为黑色
Bitmap res = new Bitmap(width, height);
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
if (vis[i, j] == ans)
{
res.SetPixel(i, j, Color.FromArgb(255, 255, 255));
}
else
{
res.SetPixel(i, j, Color.FromArgb(0, 0, 0));
}
}
}
return(new myPicture(res));
}
//输入：原图和圆心信息(圆心位置和半径)，输出：直线所在区域（包含较少噪声的圆环）
public myPicture doFind(myPicture input, circle cir)
{
int width = input.width, height = input.height;
Bitmap res = new Bitmap(width, height);
int x = (int)cir.x, y = (int)cir.y;
//截取圆环为0.15*半径——0.5*半径
int maxr = (int)(0.5 * cir.r), minr = (int)(0.15 * cir.r);
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
res.SetPixel(i, j, Color.FromArgb(255, 255, 255));
}
}
//将0.15*半径——0.5*半径区域赋值成原图像内容
for (int i = -maxr; i <= maxr; i++)
{
int pos1 = -1;
for (int j = 0; j < height; j++)
{
if (i * i + j * j <= maxr * maxr)
{
pos1 = j;
break;
}
}
int pos2 = -1;
for (int j = height - 1; j >= 0; j--)
{
if (i * i + j * j <= maxr * maxr)
{
pos2 = j;
break;
}
}
if (pos1 == -1)
{
continue;
}
for (int j = pos1; j <= pos2; j++)
{
if (i * i + j * j < minr * minr)
{
continue;
}
res.SetPixel(x + i, y + j, input.picture.GetPixel(x + i, y + j));
res.SetPixel(x + i, y - j, input.picture.GetPixel(x + i, y - j));
}
}
return(new myPicture(res));
}
public myPicture doSmooth(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 2; i + 2 < input.width; ++i)
{
for (int j = 2; j + 2 < input.height; ++j)
{
List <int> part0 = new List <int> {
input.grayDegree[i - 1, j - 2], input.grayDegree[i, j - 2], input.grayDegree[i + 1, j - 2], input.grayDegree[i - 1, j - 1], input.grayDegree[i, j - 1], input.grayDegree[i + 1, j - 1], input.grayDegree[i, j]
};
List <int> part1 = new List <int> {
input.grayDegree[i - 1, j + 2], input.grayDegree[i, j + 2], input.grayDegree[i + 1, j + 2], input.grayDegree[i - 1, j + 1], input.grayDegree[i, j + 1], input.grayDegree[i + 1, j + 1], input.grayDegree[i, j]
};
List <int> part2 = new List <int> {
input.grayDegree[i - 2, j - 1], input.grayDegree[i - 2, j], input.grayDegree[i - 2, j + 1], input.grayDegree[i - 1, j - 1], input.grayDegree[i - 1, j], input.grayDegree[i - 1, j + 1], input.grayDegree[i, j]
};
List <int> part3 = new List <int> {
input.grayDegree[i + 2, j - 1], input.grayDegree[i + 2, j], input.grayDegree[i + 2, j + 1], input.grayDegree[i + 1, j - 1], input.grayDegree[i + 1, j], input.grayDegree[i + 1, j + 1], input.grayDegree[i, j]
};
List <int> part4 = new List <int> {
input.grayDegree[i - 2, j - 2], input.grayDegree[i - 2, j - 1], input.grayDegree[i - 1, j - 2], input.grayDegree[i - 1, j - 1], input.grayDegree[i - 1, j], input.grayDegree[i, j - 1], input.grayDegree[i, j]
};
List <int> part5 = new List <int> {
input.grayDegree[i + 2, j - 2], input.grayDegree[i + 2, j - 1], input.grayDegree[i + 1, j - 2], input.grayDegree[i + 1, j - 1], input.grayDegree[i + 1, j], input.grayDegree[i, j - 1], input.grayDegree[i, j]
};
List <int> part6 = new List <int> {
input.grayDegree[i + 2, j + 2], input.grayDegree[i + 2, j + 1], input.grayDegree[i + 1, j + 2], input.grayDegree[i + 1, j + 1], input.grayDegree[i + 1, j], input.grayDegree[i, j + 1], input.grayDegree[i, j]
};
List <int> part7 = new List <int> {
input.grayDegree[i - 2, j + 2], input.grayDegree[i - 2, j + 1], input.grayDegree[i - 1, j + 2], input.grayDegree[i - 1, j + 1], input.grayDegree[i - 1, j], input.grayDegree[i, j + 1], input.grayDegree[i, j]
};
List <int> part8 = new List <int> {
input.grayDegree[i - 1, j - 1], input.grayDegree[i - 1, j], input.grayDegree[i - 1, j + 1], input.grayDegree[i, j - 1], input.grayDegree[i, j], input.grayDegree[i, j + 1], input.grayDegree[i + 1, j - 1], input.grayDegree[i + 1, j], input.grayDegree[i + 1, j + 1]
};
List <square> tmp = new List <square>();
tmp.Add(new square(part0));
tmp.Add(new square(part1));
tmp.Add(new square(part2));
tmp.Add(new square(part3));
tmp.Add(new square(part4));
tmp.Add(new square(part5));
tmp.Add(new square(part6));
tmp.Add(new square(part7));
tmp.Add(new square(part8));
tmp.Sort(new squareCmp());
int val = (int)tmp[0].average;
ret.SetPixel(i, j, Color.FromArgb(val, val, val));
}
}
return(new myPicture(ret, input.path));
}
public myPicture doSharp(myPicture input)
{
matrix mat = new matrix(3, 3);
mat.a[0, 1] = -1;
mat.a[1, 0] = -1;
mat.a[1, 1] = 4;
mat.a[1, 2] = -1;
mat.a[2, 1] = -1;
smoothTemplate smooth = new smoothTemplate();
return(smooth.doSmooth(input, mat));
}
public myPicture to01Pic()
{
myPicture ret = this;
for (int i = 0; i < width; ++i)
{
for (int j = 0; j < height; ++j)
{
int val = grayDegree[i, j];
ret.picture.SetPixel(i, j, Color.FromArgb(val, val, val));
}
}
return(ret);
}
private void 打开ToolStripMenuItem_Click(object sender, EventArgs e)
{
OpenFileDialog fileName = new OpenFileDialog();
fileName.InitialDirectory = "c:\\";
fileName.FilterIndex = 2;
fileName.RestoreDirectory = true;
if (fileName.ShowDialog() == DialogResult.OK)
{
Image pic = Image.FromFile(fileName.FileName);
Pic = new myPicture((Bitmap)pic, fileName.FileName);
this.rawPictureDisplay.Image = Pic.picture;
}
}
//输入：锐化和二值化后的图像，r是擦除时使用的半径长度，x，y是圆心位置
public findTick(myPicture Pic, int r, int x, int y)
{
width = Pic.width;
height = Pic.height;
gray = new int[width, height];
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
gray[i, j] = Pic.grayDegree[i, j];
}
}
radius = r;
circle_x = x;
circle_y = y;
}
public myPicture doSmooth(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
List <pair> tmp = new List <pair>();
for (int ii = 0; ii < 5; ++ii)
{
for (int jj = 0; jj < 5; ++jj)
{
int ni = i + dx[ii];
int nj = j + dy[jj];
if (ni == i && nj == j)
{
continue;
}
if (ni < 0 || ni >= input.width)
{
continue;
}
if (nj < 0 || nj >= input.height)
{
continue;
}
int d = input.grayDegree[ni, nj] - input.grayDegree[i, j];
if (d < 0)
{
d = -d;
}
tmp.Add(new pair(d, input.grayDegree[ni, nj]));
}
}
tmp.Sort(new pairCmp());
int sum = 0;
for (int k = 0; k < 5; ++k)
{
sum += tmp[k].y;
}
sum /= 5;
ret.SetPixel(i, j, Color.FromArgb(sum, sum, sum));
}
}
return(new myPicture(ret, input.path));
}
//输入：锐化和二值化后的图像，r是找到的圆环半径，x，y是圆心位置
public eraseCircleElement(myPicture Pic, int r, int x, int y)
{
width = Pic.width;
height = Pic.height;
gray = new int[width, height];
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
gray[i, j] = Pic.grayDegree[i, j];
}
}
res = new Bitmap(width, height);
radius = r;
circle_x = x;
circle_y = y;
}
//输入：对最大连通块锐化后的图像，即变成两个同心圆，输出：内层圆
public myPicture doHough(myPicture input)
{
int width = input.width, height = input.height;
Bitmap res = new Bitmap(width, height);
int sx = width / 2, sy = height / 2;
//找到内层圆上的一个像素点
for (int i = sx; i >= 0; i--)
{
if (input.grayDegree[i, sy] == 255)
{
sx = i;
break;
}
}
//初始化
gray = new int[width, height];
vis = new int[width, height];
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
gray[i, j] = input.grayDegree[i, j];
vis[i, j] = 0;
}
}
//dfs找内层圆
dfs(sx, sy, 1);
//修改图像
for (int i = 0; i < width; i++)
{
for (int j = 0; j < height; j++)
{
if (vis[i, j] == 1)
{
res.SetPixel(i, j, Color.FromArgb(255, 255, 255));
}
else
{
res.SetPixel(i, j, Color.FromArgb(0, 0, 0));
}
}
}
return(new myPicture(res));
}
public myPicture doSmooth(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
int cnt = 0;
List <int> tmp = new List <int>();
for (int ii = 0; ii < 3; ++ii)
{
for (int jj = 0; jj < 3; ++jj)
{
int ni = i + dx[ii];
int nj = j + dy[jj];
if (ni == i && nj == j)
{
continue;
}
if (ni < 0 || ni >= input.width)
{
continue;
}
if (nj < 0 || nj >= input.height)
{
continue;
}
++cnt;
tmp.Add(input.grayDegree[ni, nj]);
}
}
tmp.Sort();
int val = tmp[cnt / 2];
ret.SetPixel(i, j, Color.FromArgb(val, val, val));
}
}
return(new myPicture(ret, input.path));
}
public myPicture doSmooth(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
int cnt = 0;
int sum = 0;
for (int ii = 0; ii < 3; ++ii)
{
for (int jj = 0; jj < 3; ++jj)
{
int ni = i + dx[ii];
int nj = j + dy[jj];
if (ni == i && nj == j)
{
continue;
}
if (ni < 0 || ni >= input.width)
{
continue;
}
if (nj < 0 || nj >= input.height)
{
continue;
}
++cnt;
sum += input.grayDegree[ni, nj];
}
}
sum /= cnt;
ret.SetPixel(i, j, Color.FromArgb(sum, sum, sum));
}
}
return(new myPicture(ret, input.path));
}
public myPicture doSharp(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
int d1 = input.getGrayDegree(i, j) - input.getGrayDegree(i - 1, j - 1);
int d2 = input.getGrayDegree(i, j) - input.getGrayDegree(i + 1, j - 1);
if (d1 < 0)
{
d1 = -d1;
}
if (d2 < 0)
{
d2 = -d2;
}
int d = Math.Max(d1, d2);
ret.SetPixel(i, j, Color.FromArgb(d, d, d));
}
}
return(new myPicture(ret, input.path));
}
public myPicture doSharp(myPicture input)
{
Bitmap ret = new Bitmap(input.width, input.height);
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
int val1 = -5 * input.getGrayDegree(i - 1, j - 1) + 3 * input.getGrayDegree(i - 1, j) + 3 * input.getGrayDegree(i - 1, j + 1) - 5 * input.getGrayDegree(i, j - 1) + 3 * input.getGrayDegree(i, j + 1) - 5 * input.getGrayDegree(i + 1, j - 1) + 3 * input.getGrayDegree(i + 1, j) + 3 * input.getGrayDegree(i + 1, j + 1);
int val2 = +3 * input.getGrayDegree(i - 1, j - 1) + 3 * input.getGrayDegree(i - 1, j) + 3 * input.getGrayDegree(i - 1, j + 1) - 5 * input.getGrayDegree(i, j - 1) + 3 * input.getGrayDegree(i, j + 1) - 5 * input.getGrayDegree(i + 1, j - 1) - 5 * input.getGrayDegree(i + 1, j) + 3 * input.getGrayDegree(i + 1, j + 1);
int val3 = +3 * input.getGrayDegree(i - 1, j - 1) + 3 * input.getGrayDegree(i - 1, j) + 3 * input.getGrayDegree(i - 1, j + 1) + 3 * input.getGrayDegree(i, j - 1) + 3 * input.getGrayDegree(i, j + 1) - 5 * input.getGrayDegree(i + 1, j - 1) - 5 * input.getGrayDegree(i + 1, j) - 5 * input.getGrayDegree(i + 1, j + 1);
int val4 = +3 * input.getGrayDegree(i - 1, j - 1) + 3 * input.getGrayDegree(i - 1, j) + 3 * input.getGrayDegree(i - 1, j + 1) + 3 * input.getGrayDegree(i, j - 1) - 5 * input.getGrayDegree(i, j + 1) + 3 * input.getGrayDegree(i + 1, j - 1) - 5 * input.getGrayDegree(i + 1, j) - 5 * input.getGrayDegree(i + 1, j + 1);
int val5 = +3 * input.getGrayDegree(i - 1, j - 1) + 3 * input.getGrayDegree(i - 1, j) - 5 * input.getGrayDegree(i - 1, j + 1) + 3 * input.getGrayDegree(i, j - 1) - 5 * input.getGrayDegree(i, j + 1) + 3 * input.getGrayDegree(i + 1, j - 1) + 3 * input.getGrayDegree(i + 1, j) - 5 * input.getGrayDegree(i + 1, j + 1);
int val6 = +3 * input.getGrayDegree(i - 1, j - 1) - 5 * input.getGrayDegree(i - 1, j) - 5 * input.getGrayDegree(i - 1, j + 1) + 3 * input.getGrayDegree(i, j - 1) - 5 * input.getGrayDegree(i, j + 1) + 3 * input.getGrayDegree(i + 1, j - 1) + 3 * input.getGrayDegree(i + 1, j) + 3 * input.getGrayDegree(i + 1, j + 1);
int val7 = -5 * input.getGrayDegree(i - 1, j - 1) - 5 * input.getGrayDegree(i - 1, j) - 5 * input.getGrayDegree(i - 1, j + 1) + 3 * input.getGrayDegree(i, j - 1) + 3 * input.getGrayDegree(i, j + 1) + 3 * input.getGrayDegree(i + 1, j - 1) + 3 * input.getGrayDegree(i + 1, j) + 3 * input.getGrayDegree(i + 1, j + 1);
int val8 = -5 * input.getGrayDegree(i - 1, j - 1) - 5 * input.getGrayDegree(i - 1, j) + 3 * input.getGrayDegree(i - 1, j + 1) - 5 * input.getGrayDegree(i, j - 1) + 3 * input.getGrayDegree(i, j + 1) + 3 * input.getGrayDegree(i + 1, j - 1) + 3 * input.getGrayDegree(i + 1, j) + 3 * input.getGrayDegree(i + 1, j + 1);
int val = 0;
if (val1 < 0)
{
val1 = -val1;
}
if (val2 < 0)
{
val2 = -val2;
}
if (val3 < 0)
{
val3 = -val3;
}
if (val4 < 0)
{
val4 = -val4;
}
if (val5 < 0)
{
val5 = -val5;
}
if (val6 < 0)
{
val6 = -val6;
}
if (val7 < 0)
{
val7 = -val7;
}
if (val8 < 0)
{
val8 = -val8;
}
if (val1 > val)
{
val = val1;
}
if (val2 > val)
{
val = val2;
}
if (val3 > val)
{
val = val3;
}
if (val4 > val)
{
val = val4;
}
if (val5 > val)
{
val = val5;
}
if (val6 > val)
{
val = val6;
}
if (val7 > val)
{
val = val7;
}
if (val8 > val)
{
val = val8;
}
if (val > 255)
{
val = 255;
}
ret.SetPixel(i, j, Color.FromArgb(val, val, val));
}
}
return(new myPicture(ret, input.path));
}
//利用OTSU算法实现二值化
//输入：input为灰度图像
//输出：res为二值图像
//选取的阈值使分割出的两类像素，类间方差最大，类内方差最小
public myPicture doOTSU(myPicture input)
{
Bitmap res = new Bitmap(input.width, input.height);
int [,,] count = new int[40, 40, 256];
int MAGIC = 300;
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
count[i / MAGIC, j / MAGIC, input.grayDegree[i, j]]++;
}
}
for (int i = 0; i < input.width; i += MAGIC)
{
for (int j = 0; j < input.height; j += MAGIC)
{
int ii = i / MAGIC;
int jj = j / MAGIC;
double n1, n2, n, sum1, sum2, sum;
n1 = 0;
n = 0;
sum1 = 0;
sum = 0;
for (int t = 0; t < 256; ++t)
{
int val = count[ii, jj, t];
sum += 1.0 * t * val;
n += val;
}
double maxVal = -1.0;
int threshold = -1;
for (int t = 0; t < 256; ++t)
{
int val = count[ii, jj, t];
n1 += val;
if (n1 == 0)
{
continue;
}
n2 = n - n1;
if (n2 == 0)
{
break;
}
sum1 += 1.0 * t * val;
sum2 = sum - sum1;
double m1 = sum1 / n1;
double m2 = sum2 / n2;
double tmp = n1 * n2 * (m1 - m2) * (m1 - m2);
if (tmp > maxVal)
{
maxVal = tmp;
threshold = t;
}
}
for (int p = i; p < Math.Min(i + MAGIC, input.width); ++p)
{
for (int q = 0; q < Math.Min(j + MAGIC, input.height); ++q)
{
if (input.grayDegree[p, q] <= threshold)
{
res.SetPixel(p, q, Color.FromArgb(0, 0, 0));
}
else
{
res.SetPixel(p, q, Color.FromArgb(255, 255, 255));
}
}
}
}
}
return(new myPicture(res));
}
//计算圆的圆心，输入为自定义图片类input，输出为三元组(x,y,r)
//对input的限制：只包含单圆环
public circle doFind(myPicture input)
{
//从圆周上对称取10组点
int cnt = 0;
LinkedList <myPair> arr = new LinkedList <myPair>();
for (int i = 2; i < input.width; i += 8)
{
for (int j = 5; j < input.height; ++j)
{
if (input.grayDegree[i, j] == 255)
{
cnt++;
arr.AddLast(new myPair(i, j));
for (int k = input.height - 5; k >= 0; --k)
{
if (input.grayDegree[i, k] == 255)
{
arr.AddLast(new myPair(i, k));
break;
}
}
break;
}
}
if (cnt == 10)
{
break;
}
}
//最小二乘法求解圆心
A = new matrix(2 * cnt, 3);
AT = new matrix(3, 2 * cnt);
B = new matrix(2 * cnt, 1);
int cur = 0;
foreach (myPair p in arr)
{
int x = p.x;
int y = p.y;
A.a[cur, 0] = x;
A.a[cur, 1] = y;
A.a[cur, 2] = 1;
AT.a[0, cur] = x;
AT.a[1, cur] = y;
AT.a[2, cur] = 1;
B.a[cur, 0] = 1.0 * x * x + 1.0 * y * y;
cur++;
}
matrix coef = AT.doMul(A);
matrix b = AT.doMul(B);
matrix mat = new matrix(3, 4);
for (int i = 0; i < 3; ++i)
{
for (int j = 0; j < 3; ++j)
{
mat.a[i, j] = coef.a[i, j];
}
}
mat.a[0, 3] = b.a[0, 0];
mat.a[1, 3] = b.a[1, 0];
mat.a[2, 3] = b.a[2, 0];
return(cal(mat));
}
public inPut(myPicture _Pic)
{
Pic = _Pic;
InitializeComponent();
}
//函数功能：对main.cs传入的图像进行处理，并将结果传递到ans.cs显示
public void domain()
{
//处理输入
double low = 0.0;
double high = 1.0;
try
{
low = Convert.ToDouble(smallInput.Text);
high = Convert.ToDouble(largeInput.Text);
}
catch
{
return;
}
OTSU B = new OTSU();
//锐化、二值化
myPicture ret = B.doOTSU(sharp4.doSharp(Pic));
myPicture res = ret;
//找圆心之前的预处理
findCircleInit circle = new findCircleInit();
ret = circle.init(ret);
ret = sharp4.doSharp(ret);
ret = circle.doHough(ret);
//找圆心
circle o = new findCircleCenter().doFind(ret);
//找指针
ret = new findLineInit().doFind(Pic, o);
myPicture tmp = sharp1.doSharp(ret);
tmp = smooth2.doSmooth(tmp);
tmp = B.doOTSU(tmp);
RANSAC R = new RANSAC();
myPair L = R.doFind(smooth2.doSmooth(B.doOTSU(sharp4.doSharp(Pic))), R.doRANSAC(tmp, new myPair((int)o.x, (int)o.y)), o);
//找刻度线的预处理
eraseCircleElement ECE = new eraseCircleElement(res, (int)o.r, (int)o.x, (int)o.y);
int r = ECE.solve();
res = ECE.erase(r - 1);
//找到左右两端的刻度线
findTick ticks = new findTick(res, r - 1, (int)o.x, (int)o.y);
myPair left = ticks.FindLeft(), right = ticks.FindRight();
//求角度
double thta = 2 * Math.PI - angle(left, right, o);
double alpha;
if (L.x <= o.x)
{
alpha = angle(left, L, o);
}
else
{
alpha = thta - angle(L, right, o);
}
double ans = low + (high - low) * (alpha + Math.PI / 180) / thta;
Form newForm = new ans(ans);
newForm.ShowDialog();
newForm.Dispose();
}
//函数功能：确定仪表盘指针的方向向量
//输入：二值图像input，直线方程ret，仪表盘中心o
//输出：仪表盘指针上的某一个点
public myPair doFind(myPicture input, line ret, circle o)
{
if (Math.Abs(ret.B) < 0.000001)
{
return(new myPair((int)o.x, 0));
}
int MAGIC = (int)(input.width * 0.18);
int cnt1 = 0, cnt2 = 0;
double K = -ret.A / ret.B;
double B = -ret.C / ret.B;
for (int dx = 1; dx <= MAGIC; ++dx)
{
double x = o.x + dx;
double y = K * x + B;
int xx = (int)x;
int yy = (int)y;
if (xx + 2 >= input.width || xx - 2 < 0)
{
break;
}
if (yy + 2 >= input.height || yy - 2 < 0)
{
break;
}
for (int i = -2; i <= 2; ++i)
{
for (int j = -2; j <= 2; ++j)
{
if (input.grayDegree[(int)(x + i), (int)(y + j)] == 255)
{
cnt1++;
}
}
}
}
for (int dx = 1; dx <= MAGIC; ++dx)
{
double x = o.x - dx;
double y = K * x + B;
int xx = (int)x;
int yy = (int)y;
if (xx + 2 >= input.width || xx - 2 < 0)
{
break;
}
if (yy + 2 >= input.height || yy - 2 < 0)
{
break;
}
for (int i = -2; i <= 2; ++i)
{
for (int j = -2; j <= 2; ++j)
{
if (input.grayDegree[(int)(x + i), (int)(y + j)] == 255)
{
cnt2++;
}
}
}
}
if (cnt1 > cnt2)
{
double x = o.x + MAGIC;
double y = K * x + B;
return(new myPair((int)x, (int)y));
}
else
{
double x = o.x - MAGIC;
double y = K * x + B;
return(new myPair((int)x, (int)y));
}
}
//函数功能：利用RANSAC算法从图像中提取直线，RANSAC对噪声敏感度小
//输入：二值化图像input，目标直线的一个端点center
//输出：目标直线方程
public line doRANSAC(myPicture input, myPair center)
{
LinkedList <myPair> arr = new LinkedList <myPair>();
for (int i = 0; i < input.width; ++i)
{
for (int j = 0; j < input.height; ++j)
{
if (input.grayDegree[i, j] == 255)
{
arr.AddLast(new myPair(i, j));
}
}
}
Random rd = new Random(13);
line ret = new line(0, 0, 0);
double besterror = 1000000000000;
int bound = (int)(0.07 * arr.Count);
for (int iter = 0; iter < 100; ++iter)
{
int sampleIndex = rd.Next() % arr.Count;
myPair sample = arr.ElementAt(sampleIndex);
line cur = new line(center, sample);
LinkedList <myPair> alsoinliers = new LinkedList <myPair>();
foreach (myPair p in arr)
{
double d = cur.distance(p);
if (d <= 4)
{
alsoinliers.AddLast(p);
}
}
if (alsoinliers.Count >= bound)
{
alsoinliers.AddLast(sample);
line better = calLine(alsoinliers);
double thiserror = 0;
foreach (myPair p in alsoinliers)
{
double dis = better.distance(p);
thiserror += dis * dis;
}
thiserror /= alsoinliers.Count;
if (thiserror < besterror)
{
besterror = thiserror;
ret = better;
}
}
}
return(ret);
/*
* for (int i = 0; i < input.width; ++i)
* {
* for (int j = 0; j < input.height; ++j)
* {
* double val = Math.Abs(ret.A * i + ret.B * j + ret.C);
* if (val <= 1)
* {
* input.picture.SetPixel(i, j, Color.FromArgb(255, 0, 0));
* }
* }
* }
*/
//return input;
}
