链码边界提取 python 边界链码算法过程

链码在图像提取的后期即模式识别是一个很重要的特征，比如进行数字识别或者文字识别都会用到链码的特征，而链码的提取则可以借助于边界跟踪算法获取边界序列，注意是边界序列而不是边界，边界很容易获取，但是要想把边界的点按照一定的顺序输出则要费些功夫。下面采用边界跟踪算法获取边界，并存储在堆栈中，（这里的堆栈实际是C++容器类，是虚拟堆栈）。


利用点的八邻域信息，选择下一个点作为边界点，这个算法需要选择一个开始点，可以选择图像上是目标点，在最上，最左的点。然后查看它的八邻域的点，从右下方45°的位置开始寻找，如果是目标点，将沿顺时针90°作为下一次寻找的方向，如果不是，则逆时针45°继续寻找，一旦找到重复上面的过程。

具体的步骤在算法中有讲解。

/************************************************************************/
/* 查找物体的边界，输出已排序的边界序列 适应于单一区域        */
/************************************************************************/
//若能够输出边界点的序列则是比较有用的
#include<cv.h>
#include <highgui.h>
#include <iostream>
#include <stack>
using namespace std;



int main(){ 
	IplImage * image,*image2;
	image = cvLoadImage("E:\\image\\mapleleaf.tif",0);
	cvNamedWindow("image",1);
	cvShowImage("image",image);

	image2 = cvCreateImage(cvSize(image->width, image->height),image->depth,1);
	cvZero(image2);//image2 赋值为0
	//寻找区域的左上角点
	CvPoint startPoint = cvPoint(0,0);
	bool bFindStartpoint = false;
	int i ,j;
	unsigned char * ptr,*dst;
	stack<int> board;//奇数位存储x坐标，偶数位存储y坐标

	//当前扫描点
	CvPoint currentPoint = cvPoint(0,0);
	//邻域的8个点的方向
	int directions[8][2] = {{0,1},{1,1},{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1}}; 
	int beginDirection = 0;
	bool bFindBoardpoint = false;//寻找到邻域的边界点的判定
	for (i = 0 ; i< image->height && bFindStartpoint == false; i++)
	{
		for (j = 0 ; j< image->width && bFindStartpoint == false; j++)
		{
			ptr = (unsigned char *)(image->imageData + i*image->widthStep + j);
			if (*ptr == 255)
			{
				startPoint.x = j;
				startPoint.y = i;
				bFindStartpoint = true;
				//cout<<"x:  " << j <<"y :  " <<i <<endl;  
			}
		}
	}

	//进行边界跟踪 每次搜索8个方向的点 找到了即停止
	currentPoint = startPoint;
    bFindStartpoint = false;
	beginDirection = 0;
	board.push(startPoint.x);
	board.push(startPoint.y);
	while (!bFindStartpoint)
	{
		bFindBoardpoint = false;
		//在8个方向寻找符合条件的边界点
		while (!bFindBoardpoint)
		{   
			//进行出界判定  不对啊 这张图不可能出界啊
			ptr = (unsigned char *)(image->imageData + (currentPoint.y + directions[beginDirection][1])* image->widthStep + currentPoint.x + directions[beginDirection][0]);
			if (*ptr == 255)
			{
				bFindBoardpoint = true;
				currentPoint.x +=  directions[beginDirection][0];
				currentPoint.y  += directions[beginDirection][1];
				/************************************************************************/
				/*  此处添加序列存储的代码                    */
				/************************************************************************/
				//一、将边界存储到图片中
				dst  = (unsigned char *)image2->imageData + currentPoint.y * image2->widthStep + currentPoint.x;
				*dst = 255;

				//二、将边界点的序列存储到一个堆栈中
				board.push(currentPoint.x);
				board.push(currentPoint.y);

				if (currentPoint.x == startPoint.x  && currentPoint.y == startPoint.y )
				{
					bFindStartpoint = true;
				}
				//改变下次首先开始扫描的方向
				beginDirection -= 2;
				if (beginDirection < 0)
				{
					beginDirection += 8;
				}
				
				
				
			}
			else
			{
				beginDirection ++;
				beginDirection = beginDirection%8;
			}
		}
		//cout<<"currentPoint    "<<currentPoint.x <<"     "<< currentPoint.y<<endl;
	}
	cvNamedWindow("image2",1);
	cvShowImage("image2",image2);
	

	//显示堆栈中的数据 顺时针存储,逆时针显示
	//注意：显示时候堆栈中已经没有数据了
/*	int x,y;
	while(!board.empty())
	{
		y = board.top();
		board.pop();
		x = board.top();
		board.pop();
		cout<<"x   "<<x<<"    y    "<<y<<endl;
	}
*/
	cvWaitKey(0);
	return 0;
}

/************************************************************************/
/* 轮廓跟踪算法获取物体的轮廓序列 生成边界链码   */
/************************************************************************/
#include<cv.h>
#include <highgui.h>
#include <iostream>
#include <stack>
using namespace std;



int main(){ 
	IplImage * image,*image2,*image3;
	image = cvLoadImage("E:\\image\\bottle2.tif",0);
	cvNamedWindow("image",1);
	cvShowImage("image",image);

	image2 = cvCreateImage(cvSize(image->width, image->height),image->depth,1);
	image3 = cvCreateImage(cvSize(image->width, image->height),image->depth,1);
	cvZero(image2);//image2 赋值为0
	cvZero(image3);
	//寻找区域的左上角点
	CvPoint startPoint = cvPoint(0,0);
	bool bFindStartpoint = false;
	int i ,j;
	unsigned char * ptr,*dst;
	stack<int> board;//奇数位存储x坐标，偶数位存储y坐标

	//当前扫描点
	CvPoint currentPoint = cvPoint(0,0);
	//邻域的8个点的方向
	int directions[8][2] = {{0,1},{1,1},{1,0},{1,-1},{0,-1},{-1,-1},{-1,0},{-1,1}}; 
	int beginDirection = 0;
	bool bFindBoardpoint = false;//寻找到邻域的边界点的判定
	for (i = 0 ; i< image->height && bFindStartpoint == false; i++)
	{
		for (j = 0 ; j< image->width && bFindStartpoint == false; j++)
		{
			ptr = (unsigned char *)(image->imageData + i*image->widthStep + j);
			if (*ptr == 255)
			{
				startPoint.x = j;
				startPoint.y = i;
				bFindStartpoint = true;
				//cout<<"x:  " << j <<"y :  " <<i <<endl;  
			}
		}
	}

	//进行边界跟踪 每次搜索8个方向的点 找到了即停止
	currentPoint = startPoint;
    bFindStartpoint = false;
	beginDirection = 0;
	board.push(startPoint.x);
	board.push(startPoint.y);
	while (!bFindStartpoint)
	{
		bFindBoardpoint = false;
		//在8个方向寻找符合条件的边界点
		while (!bFindBoardpoint)
		{   
			//进行出界判定  不对啊 这张图不可能出界啊
			ptr = (unsigned char *)(image->imageData + (currentPoint.y + directions[beginDirection][1])* image->widthStep + currentPoint.x + directions[beginDirection][0]);
			if (*ptr == 255)
			{
				bFindBoardpoint = true;
				currentPoint.x +=  directions[beginDirection][0];
				currentPoint.y  += directions[beginDirection][1];
				/************************************************************************/
				/*  此处添加序列存储的代码                    */
				/************************************************************************/
				//一、将边界存储到图片中
				dst  = (unsigned char *)image2->imageData + currentPoint.y * image2->widthStep + currentPoint.x;
				*dst = 255;

				//二、将边界点的序列存储到一个堆栈中
				board.push(currentPoint.x);
				board.push(currentPoint.y);

				if (currentPoint.x == startPoint.x  && currentPoint.y == startPoint.y )
				{
					bFindStartpoint = true;
				}
				//改变下次首先开始扫描的方向
				beginDirection -= 2;
				if (beginDirection < 0)
				{
					beginDirection += 8;
				}
				
				
				
			}
			else
			{
				beginDirection ++;
				beginDirection = beginDirection%8;
			}
		}
		//cout<<"currentPoint    "<<currentPoint.x <<"     "<< currentPoint.y<<endl;
	}
	cvNamedWindow("image2",1);
	cvShowImage("image2",image2);
	

	//显示堆栈中的数据 顺时针存储,逆时针显示
	//注意：显示时候堆栈中已经没有数据了
/*	int x,y;
	while(!board.empty())
	{
		y = board.top();
		board.pop();
		x = board.top();
		board.pop();
		cout<<"x   "<<x<<"    y    "<<y<<endl;
	}
*/

	//Board中存储着边界的序列 转化为8邻域链码，每隔10个点取样 显示

	int lianmaLength = (board.size()+5)/10;
    int* lianma = new int[lianmaLength];

	for (i = 0 ; i< lianmaLength  && !board.empty();i += 2)
	{
		lianma[i+1] = board.top();
		board.pop();
		lianma[i] = board.top();
		board.pop();

		for (j = 0; j< 18 && !board.empty();j++)
		{
			board.pop();
		}
	}
	//将数据在image3中显示
	int t;
	for ( t = 0; t < lianmaLength;t += 2)
	{
		 i = lianma[t+1];
		 j = lianma[t];
		 ptr = (unsigned char *)image3->imageData + i*image->widthStep + j;
		 *ptr = 255;
		
	}
    cvNamedWindow("image3",1);
	cvSaveImage("E:\\image\\bottle2lianma.bmp",image3);
	cvShowImage("image3",image3);


	cvWaitKey(0);
	return 0;
}