图像处理基本算法 链码 边界跟踪
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 = {{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)* image->widthStep + currentPoint.x + directions);
if (*ptr == 255)
{
bFindBoardpoint = true;
currentPoint.x +=directions;
currentPoint.y+= directions;
/************************************************************************/
/*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;
}
http://hi.csdn.net/attachment/201202/11/0_1328947268vbFT.gif
http://hi.csdn.net/attachment/201202/11/0_1328947275Tat9.gif
/************************************************************************//* 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 = {{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)* image->widthStep + currentPoint.x + directions);
if (*ptr == 255)
{
bFindBoardpoint = true;
currentPoint.x +=directions;
currentPoint.y+= directions;
/************************************************************************/
/*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;
for (i = 0 ; i< lianmaLength&& !board.empty();i += 2)
{
lianma = board.top();
board.pop();
lianma = 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;
j = lianma;
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;
}
作者：renshengrumenglibing 发表于2012-2-11 15:58:54 原文链接
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