OpenCV实现二值图像的边缘光滑处理

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我是靠谱客的博主愤怒溪流，这篇文章主要介绍OpenCV实现二值图像的边缘光滑处理，现在分享给大家，希望可以做个参考。

本文实例为大家分享了OpenCV学习笔记之针对二值图像的边缘光滑处理（突出部消除），供大家参考，具体内容如下

处理代码分为两部分，第一部分用于去除边缘的突出部，第二部分用于边缘光滑。具体如下所示

1.去除边缘突出部

复制代码

//去除二值图像边缘的突出部
//uthreshold、vthreshold分别表示突出部的宽度阈值和高度阈值
//type代表突出部的颜色，0表示黑色，1代表白色 
void delete_jut(Mat& src, Mat& dst, int uthreshold, int vthreshold, int type)
{
 int threshold;
 src.copyTo(dst);
 int height = dst.rows;
 int width = dst.cols;
 int k; //用于循环计数传递到外部
 for (int i = 0; i < height - 1; i++)
 {
 uchar* p = dst.ptr<uchar>(i);
 for (int j = 0; j < width - 1; j++)
 {
  if (type == 0)
  {
  //行消除
  if (p[j] == 255 && p[j + 1] == 0)
  {
   if (j + uthreshold >= width)
   {
   for (int k = j + 1; k < width; k++)
    p[k] = 255;
   }
   else
   {
   for (k = j + 2; k <= j + uthreshold; k++)
   {
    if (p[k] == 255) break;
   }
   if (p[k] == 255)
   {
    for (int h = j + 1; h < k; h++)
    p[h] = 255;
   }
   }
  }
  //列消除
  if (p[j] == 255 && p[j + width] == 0)
  {
   if (i + vthreshold >= height)
   {
   for (k = j + width; k < j + (height - i)*width; k += width)
    p[k] = 255;
   }
   else
   {
   for (k = j + 2 * width; k <= j + vthreshold*width; k += width)
   {
    if (p[k] == 255) break;
   }
   if (p[k] == 255)
   {
    for (int h = j + width; h < k; h += width)
    p[h] = 255;
   }
   }
  }
  }
  else //type = 1
  {
  //行消除
  if (p[j] == 0 && p[j + 1] == 255)
  {
   if (j + uthreshold >= width)
   {
   for (int k = j + 1; k < width; k++)
    p[k] = 0;
   }
   else
   {
   for (k = j + 2; k <= j + uthreshold; k++)
   {
    if (p[k] == 0) break;
   }
   if (p[k] == 0)
   {
    for (int h = j + 1; h < k; h++)
    p[h] = 0;
   }
   }
  }
  //列消除
  if (p[j] == 0 && p[j + width] == 255)
  {
   if (i + vthreshold >= height)
   {
   for (k = j + width; k < j + (height - i)*width; k += width)
    p[k] = 0;
   }
   else
   {
   for (k = j + 2 * width; k <= j + vthreshold*width; k += width)
   {
    if (p[k] == 0) break;
   }
   if (p[k] == 0)
   {
    for (int h = j + width; h < k; h += width)
    p[h] = 0;
   }
   }
  }
  }
 }
 }
}

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//去除二值图像边缘的突出部
//uthreshold、vthreshold分别表示突出部的宽度阈值和高度阈值
//type代表突出部的颜色，0表示黑色，1代表白色 
void delete_jut(Mat& src, Mat& dst, int uthreshold, int vthreshold, int type)
{
 int threshold;
 src.copyTo(dst);
 int height = dst.rows;
 int width = dst.cols;
 int k; //用于循环计数传递到外部
 for (int i = 0; i < height - 1; i++)
 {
 uchar* p = dst.ptr<uchar>(i);
 for (int j = 0; j < width - 1; j++)
 {
  if (type == 0)
  {
  //行消除
  if (p[j] == 255 && p[j + 1] == 0)
  {
   if (j + uthreshold >= width)
   {
   for (int k = j + 1; k < width; k++)
    p[k] = 255;
   }
   else
   {
   for (k = j + 2; k <= j + uthreshold; k++)
   {
    if (p[k] == 255) break;
   }
   if (p[k] == 255)
   {
    for (int h = j + 1; h < k; h++)
    p[h] = 255;
   }
   }
  }
  //列消除
  if (p[j] == 255 && p[j + width] == 0)
  {
   if (i + vthreshold >= height)
   {
   for (k = j + width; k < j + (height - i)*width; k += width)
    p[k] = 255;
   }
   else
   {
   for (k = j + 2 * width; k <= j + vthreshold*width; k += width)
   {
    if (p[k] == 255) break;
   }
   if (p[k] == 255)
   {
    for (int h = j + width; h < k; h += width)
    p[h] = 255;
   }
   }
  }
  }
  else //type = 1
  {
  //行消除
  if (p[j] == 0 && p[j + 1] == 255)
  {
   if (j + uthreshold >= width)
   {
   for (int k = j + 1; k < width; k++)
    p[k] = 0;
   }
   else
   {
   for (k = j + 2; k <= j + uthreshold; k++)
   {
    if (p[k] == 0) break;
   }
   if (p[k] == 0)
   {
    for (int h = j + 1; h < k; h++)
    p[h] = 0;
   }
   }
  }
  //列消除
  if (p[j] == 0 && p[j + width] == 255)
  {
   if (i + vthreshold >= height)
   {
   for (k = j + width; k < j + (height - i)*width; k += width)
    p[k] = 0;
   }
   else
   {
   for (k = j + 2 * width; k <= j + vthreshold*width; k += width)
   {
    if (p[k] == 0) break;
   }
   if (p[k] == 0)
   {
    for (int h = j + width; h < k; h += width)
    p[h] = 0;
   }
   }
  }
  }
 }
 }
}

效果如下：

2.边缘光滑处理

复制代码

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//图片边缘光滑处理
//size表示取均值的窗口大小，threshold表示对均值图像进行二值化的阈值
void imageblur(Mat& src, Mat& dst, Size size, int threshold)
{
 int height = src.rows;
 int width = src.cols;
 blur(src, dst, size);
 for (int i = 0; i < height; i++)
 {
 uchar* p = dst.ptr<uchar>(i);
 for (int j = 0; j < width; j++)
 {
  if (p[j] < threshold) 
  p[j] = 0;
  else p[j] = 255;
 }
 }
 imshow("Blur", dst);
}