OpenCV学习笔记之针对二值图像的边缘光滑处理（突出部消除）

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

//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(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

//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(i);
		for (int j = 0; j < width; j++)
		{
			if (p[j] < threshold) 
				p[j] = 0;
			else p[j] = 255;
		}
	}
	imshow("Blur", dst);
}

效果如下：