自己用C#写的图像细化算法，输入图像为Bitmap类型，输出也是同样的类型，注意<pre name="code" class="csharp">ToThinner(Bitmap srcImg)
中的输入图像srcImg必须为像素0和255的二值化的图像。
public unsafe Bitmap ToThinner(Bitmap srcImg)
{
int iw = srcImg.Width;
int ih = srcImg.Height;
bool bModified; //二值图像修改标志
bool bCondition1; //细化条件1标志
bool bCondition2; //细化条件2标志
bool bCondition3; //细化条件3标志
bool bCondition4; //细化条件4标志
int nCount;
//5X5像素块
byte[,] neighbour = new byte[5, 5];
//新建临时存储图像
Bitmap NImg = new Bitmap(iw, ih, srcImg.PixelFormat);
bModified = true; //细化修改标志, 用作循环条件
BitmapData dstData = srcImg.LockBits(new Rectangle(0, 0, iw, ih), ImageLockMode.ReadWrite, srcImg.PixelFormat);
byte* data = (byte*)(dstData.Scan0);
//将图像转换为0,1二值得图像;
int step = dstData.Stride;
for (int i = 0; i < dstData.Height; i++)
{
for (int j = 0; j < dstData.Width; j++)
{
if (data[i * step + j] > 128)
data[i * step + j] = 0;
else
data[i * step + j] = 1;
}
}
BitmapData dstData1 = NImg.LockBits(new Rectangle(0, 0, iw, ih), ImageLockMode.ReadWrite, NImg.PixelFormat);
byte* data1 = (byte*)(dstData1.Scan0);
int step1 = dstData1.Stride;
//细化循环开始
while (bModified)
{
bModified = false;
//初始化临时二值图像NImg
for (int i = 0; i < dstData1.Height; i++)
{
for (int j = 0; j < dstData1.Width; j++)
{
data1[i * step1 + j] = 0;
}
}
for (int i = 2; i < ih - 2; i++)
{
for (int j = 2; j < iw - 2; j++)
{
bCondition1 = false;
bCondition2 = false;
bCondition3 = false;
bCondition4 = false;
if (data[i * step + j] == 0) //若图像的当前点为白色，则跳过
continue;
for (int k = 0; k < 5; k++)
{
//取以当前点为中心的5X5块
for (int l = 0; l < 5; l++)
{
//1代表黑色, 0代表白色
//neighbour[k, l] = bw[i + k - 2, j + l - 2];
neighbour[k, l] = data[(i + k - 2) * step + (j + l - 2)];
}
}
//(1)判断条件2<=n(p)<=6
nCount = neighbour[1, 1] + neighbour[1, 2] + neighbour[1, 3] +
neighbour[2, 1] + neighbour[2, 3] +
neighbour[3, 1] + neighbour[3, 2] + neighbour[3, 3];
if (nCount >= 2 && nCount <= 6)
bCondition1 = true;
else
{
data1[i * step1 + j] = 1;
continue; //跳过, 加快速度
}
//(2)判断s(p)=1
nCount = 0;
if (neighbour[2, 3] == 0 && neighbour[1, 3] == 1)
nCount++;
if (neighbour[1, 3] == 0 && neighbour[1, 2] == 1)
nCount++;
if (neighbour[1, 2] == 0 && neighbour[1, 1] == 1)
nCount++;
if (neighbour[1, 1] == 0 && neighbour[2, 1] == 1)
nCount++;
if (neighbour[2, 1] == 0 && neighbour[3, 1] == 1)
nCount++;
if (neighbour[3, 1] == 0 && neighbour[3, 2] == 1)
nCount++;
if (neighbour[3, 2] == 0 && neighbour[3, 3] == 1)
nCount++;
if (neighbour[3, 3] == 0 && neighbour[2, 3] == 1)
nCount++;
if (nCount == 1)
bCondition2 = true;
else
{
data1[i * step1 + j] = 1;
continue;
}
//(3)判断p0*p2*p4=0 or s(p2)!=1
if (neighbour[2, 3] * neighbour[1, 2] * neighbour[2, 1] == 0)
bCondition3 = true;
else
{
nCount = 0;
if (neighbour[0, 2] == 0 && neighbour[0, 1] == 1)
nCount++;
if (neighbour[0, 1] == 0 && neighbour[1, 1] == 1)
nCount++;
if (neighbour[1, 1] == 0 && neighbour[2, 1] == 1)
nCount++;
if (neighbour[2, 1] == 0 && neighbour[2, 2] == 1)
nCount++;
if (neighbour[2, 2] == 0 && neighbour[2, 3] == 1)
nCount++;
if (neighbour[2, 3] == 0 && neighbour[1, 3] == 1)
nCount++;
if (neighbour[1, 3] == 0 && neighbour[0, 3] == 1)
nCount++;
if (neighbour[0, 3] == 0 && neighbour[0, 2] == 1)
nCount++;
if (nCount != 1) //s(p2)!=1
bCondition3 = true;
else
{
data1[i * step1 + j] = 1;
continue;
}
}
//(4)判断p2*p4*p6=0 or s(p4)!=1
if (neighbour[1, 2] * neighbour[2, 1] * neighbour[3, 2] == 0)
bCondition4 = true;
else
{
nCount = 0;
if (neighbour[1, 1] == 0 && neighbour[1, 0] == 1)
nCount++;
if (neighbour[1, 0] == 0 && neighbour[2, 0] == 1)
nCount++;
if (neighbour[2, 0] == 0 && neighbour[3, 0] == 1)
nCount++;
if (neighbour[3, 0] == 0 && neighbour[3, 1] == 1)
nCount++;
if (neighbour[3, 1] == 0 && neighbour[3, 2] == 1)
nCount++;
if (neighbour[3, 2] == 0 && neighbour[2, 2] == 1)
nCount++;
if (neighbour[2, 2] == 0 && neighbour[1, 2] == 1)
nCount++;
if (neighbour[1, 2] == 0 && neighbour[1, 1] == 1)
nCount++;
if (nCount != 1)//s(p4)!=1
bCondition4 = true;
}
if (bCondition1 && bCondition2 && bCondition3 && bCondition4)
{
data1[i * step1 + j] = 0;
bModified = true;
}
else
{
data1[i * step1 + j] = 1;
}
}
}
//将细化了的临时图像bw_tem[w,h]copy到bw[w,h],完成一次细化
for (int i = 2; i < ih - 2; i++)
for (int j = 2; j < iw - 2; j++)
data[i * step + j] = data1[i * step1 + j];
}
for (int i = 2; i < ih - 2; i++)
{
for (int j = 2; j < iw - 2; j++)
{
if (data[i * step + j] == 1)
data[i * step + j] = 0;
else
data[i * step + j] = 255;
}
}
srcImg.UnlockBits(dstData);
NImg.UnlockBits(dstData1);
return (srcImg);
}
<img src="http://img.blog.csdn.net/20140813102748875?watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQvbW9vbmxpZ2h0cmFu/font/5a6L5L2T/fontsize/400/fill/I0JBQkFCMA==/dissolve/70/gravity/SouthEast" alt="" />
如上图就是用细化算法细化的图像。
</pre>
C#写的图像细化算法
时间： 2024-08-03 06:33:55