1. 用OpenCV验证腐蚀和膨胀,只需截图回复。具体做法可参考何东健课件和源代码的第6章或其他资源。
2. 用OpenCV验证细化,只需截图回复。具体做法可参考何东健课件和源代码的第6章或其他资源。
3. 其他方法,可先了解基本原理,数学推导知道即可。
算法理论文章: https://blog.csdn.net/baidu_21578557/article/details/51871134
用OpenCV验证腐蚀和膨胀
public class threshold {
private final static String path = System.getProperty("user.dir") + "\\catton.jpg";
static {
platformUtils.loadLibraries();
}
public static void main(String[] args) {
Mat src= Imgcodecs.imread(path);
Mat dest=new Mat();
Imgproc.threshold(src,dest,100,500,Imgproc.THRESH_BINARY);
//获取数据
byte [] data=new byte[dest.rows()*dest.cols()*(int)dest.elemSize()];
dest.get(0,0,data);
//转为二值化image buffer作为存储对象 可以存储二进制 也可以存储灰度化图像
BufferedImage bufferedImage=new BufferedImage(dest.cols(),dest.rows(),BufferedImage.TYPE_BYTE_GRAY);
bufferedImage.getRaster().setDataElements(0,0,dest.cols(),dest.rows(),data);
JFrame frame=new JFrame();
frame.getContentPane().add(new JLabel(new ImageIcon(bufferedImage)));
frame.pack();
frame.setVisible(true);
HighGui.imshow(" threshold image",dest);
HighGui.waitKey(0);
}
}
用OpenCV验证细化
//提取图像的骨架
void ImgThin(cv::Mat src,int maxIterations=-1)
{
if (src.empty()) return;//图像为空,直接返回
cv::threshold(src, src, m_dThreshold, 1, CV_THRESH_BINARY);//转为0或1的图像
int ImgHeight = src.rows;
int ImgWidth = src.cols;
int count = 0; //记录迭代次数
while (true)
{
count++;
if (maxIterations != -1 && count > maxIterations) //限制次数并且迭代次数到达
break;
vector<pair<int, int> > mFlag; //用于标记需要删除的点
//对点标记
for (int i = 0; i < ImgHeight; ++i)
{
for (int j = 0; j < ImgWidth; ++j)
{
//如果满足四个条件,进行标记
// p9 p2 p3
// p8 p1 p4
// p7 p6 p5
int p1 = src.at<uchar>(i, j);
int p2 = (i == 0) ? 0 : src.at<uchar>(i - 1, j);
int p3 = (i == 0 || j == ImgWidth - 1) ? 0 : src.at<uchar>(i - 1, j + 1);
int p4 = (j == ImgWidth - 1) ? 0 : src.at<uchar>(i, j + 1);
int p5 = (i == ImgHeight - 1 || j == ImgWidth - 1) ? 0 : src.at<uchar>(i + 1, j + 1);
int p6 = (i == ImgHeight - 1) ? 0 : src.at<uchar>(i + 1, j);
int p7 = (i == ImgHeight - 1 || j == 0) ? 0 : src.at<uchar>(i + 1, j - 1);
int p8 = (j == 0) ? 0 : src.at<uchar>(i, j - 1);
int p9 = (i == 0 || j == 0) ? 0 : src.at<uchar>(i - 1, j - 1);
if ((p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9) >= 2 && (p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9) <= 6)
{
int ap = 0;
if (p2 == 0 && p3 == 1) ++ap;
if (p3 == 0 && p4 == 1) ++ap;
if (p4 == 0 && p5 == 1) ++ap;
if (p5 == 0 && p6 == 1) ++ap;
if (p6 == 0 && p7 == 1) ++ap;
if (p7 == 0 && p8 == 1) ++ap;
if (p8 == 0 && p9 == 1) ++ap;
if (p9 == 0 && p2 == 1) ++ap;
if (ap == 1)
{
if (p2*p4*p6 == 0)
{
if (p4*p6*p8 == 0)
{
//标记
mFlag.push_back(make_pair(i, j));
}
}
}
}
}
}
//将标记的点删除
for (vector<pair<int, int> >::iterator i = mFlag.begin(); i != mFlag.end(); ++i)
{
src.at<uchar>(i->first, i->second) = 0;
}
//直到没有点满足,算法结束
if (mFlag.size() == 0) break;
else mFlag.clear();//将mFlag清空
//对点标记
for (int i = 0; i < ImgHeight; ++i)
{
for (int j = 0; j < ImgWidth; ++j)
{
//如果满足四个条件,进行标记
// p9 p2 p3
// p8 p1 p4
// p7 p6 p5
int p1 = src.at<uchar>(i, j);
if (p1 != 1) continue;
int p2 = (i == 0) ? 0 : src.at<uchar>(i - 1, j);
int p3 = (i == 0 || j == ImgWidth - 1) ? 0 : src.at<uchar>(i - 1, j + 1);
int p4 = (j == ImgWidth - 1) ? 0 : src.at<uchar>(i, j + 1);
int p5 = (i == ImgHeight - 1 || j == ImgWidth - 1) ? 0 : src.at<uchar>(i + 1, j + 1);
int p6 = (i == ImgHeight - 1) ? 0 : src.at<uchar>(i + 1, j);
int p7 = (i == ImgHeight - 1 || j == 0) ? 0 : src.at<uchar>(i + 1, j - 1);
int p8 = (j == 0) ? 0 : src.at<uchar>(i, j - 1);
int p9 = (i == 0 || j == 0) ? 0 : src.at<uchar>(i - 1, j - 1);
if ((p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9) >= 2 && (p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9) <= 6)
{
int ap = 0;
if (p2 == 0 && p3 == 1) ++ap;
if (p3 == 0 && p4 == 1) ++ap;
if (p4 == 0 && p5 == 1) ++ap;
if (p5 == 0 && p6 == 1) ++ap;
if (p6 == 0 && p7 == 1) ++ap;
if (p7 == 0 && p8 == 1) ++ap;
if (p8 == 0 && p9 == 1) ++ap;
if (p9 == 0 && p2 == 1) ++ap;
if (ap == 1)
{
if (p2*p4*p8 == 0)
{
if (p2*p6*p8 == 0)
{
//标记
mFlag.push_back(make_pair(i, j));
}
}
}
}
}
}
//删除
for (vector<pair<int, int> >::iterator i = mFlag.begin(); i != mFlag.end(); ++i)
{
src.at<uchar>(i->first, i->second) = 0;
}
//直到没有点满足,算法结束
if (mFlag.size() == 0) break;
else mFlag.clear();//将mFlag清空
}
cv::threshold(src, src, 0, 255, CV_THRESH_BINARY);//二值化图像
}