【OpenCV图像处理】激光条纹线段提取、中心线提取
#include
#include
#include
#include
using namespace std;
using namespace cv;
//-----------------------------------【全局变量声明部分】--------------------------------------
// 描述：全局变量声明
//-----------------------------------------------------------------------------------------------
Mat g_srcImage, g_dstImage, g_midImage, g_grayImage, imgHSVMask;//原始图、中间图和效果图
int threshold_value = 60; //阈值
int size = 800; //面积因子
float start_time,end_time,sum_time; //处理时间
//-----------------------------------【全局函数声明部分】--------------------------------------
// 描述：全局函数声明
//-----------------------------------------------------------------------------------------------
void ThinSubiteration1(Mat & pSrc, Mat & pDst);
void ThinSubiteration2(Mat & pSrc, Mat & pDst);
void normalizeLetter(Mat & inputarray, Mat & outputarray);
void Line_reflect(Mat & inputarray, Mat & outputarray);
void Delete_smallregions(Mat & pSrc, Mat & pDst);
//-----------------------------------【main( )函数】--------------------------------------------
// 描述：控制台应用程序的入口函数，我们的程序从这里开始
//-----------------------------------------------------------------------------------------------
int main( )
{
//载入原始图
g_srcImage = imread("3.jpg"); //读取素材图
start_time = getTickCount(); //开始处理时间
//显示灰度图
cvtColor(g_srcImage, g_grayImage, CV_RGB2GRAY);
imshow("【灰度图】", g_grayImage);
//二值化
threshold(g_grayImage, imgHSVMask, threshold_value, 255, THRESH_BINARY);
g_midImage = Mat::zeros(imgHSVMask.size(), CV_8UC1); //绘制
//去除小面积区域
Delete_smallregions(imgHSVMask, g_midImage);
imshow("【目标图】", g_midImage);
imwrite("Target_image3.jpg", g_midImage);
//normalizeLetter显示效果图
normalizeLetter(g_midImage,g_dstImage);
imshow("【效果图】", g_dstImage);
//曲线映射到原图
/* threshold(g_grayImage, g_midImage, threshold_value, 255, CV_THRESH_BINARY); */
/* imshow("【二值化图】", g_midImage); */
Line_reflect(g_dstImage,g_midImage);
imshow("【映射图】", g_midImage);
imwrite("Reflect_image3.jpg", g_midImage);
//转换类型，保存skeleton图像
normalize(g_dstImage, g_midImage, 0, 255, NORM_MINMAX, CV_8U);
imwrite("Thinning_image3.jpg", g_midImage);
//计算运行时间
end_time = getTickCount();
sum_time = (end_time - start_time)/ getTickFrequency();
printf("%lf s",sum_time);
waitKey(0);
return 0;
}
void ThinSubiteration1(Mat & pSrc, Mat & pDst) {
int rows = pSrc.rows;
int cols = pSrc.cols;
pSrc.copyTo(pDst);
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
if(pSrc.at(i, j) == 1.0f) {
/// get 8 neighbors
/// calculate C(p)
int neighbor0 = (int) pSrc.at( i-1, j-1);
int neighbor1 = (int) pSrc.at( i-1, j);
int neighbor2 = (int) pSrc.at( i-1, j+1);
int neighbor3 = (int) pSrc.at( i, j+1);
int neighbor4 = (int) pSrc.at( i+1, j+1);
int neighbor5 = (int) pSrc.at( i+1, j);
int neighbor6 = (int) pSrc.at( i+1, j-1);
int neighbor7 = (int) pSrc.at( i, j-1);
int C = int(~neighbor1 & ( neighbor2 | neighbor3)) +
int(~neighbor3 & ( neighbor4 | neighbor5)) +
int(~neighbor5 & ( neighbor6 | neighbor7)) +
int(~neighbor7 & ( neighbor0 | neighbor1));
if(C == 1) {
/// calculate N
int N1 = int(neighbor0 | neighbor1) +
int(neighbor2 | neighbor3) +
int(neighbor4 | neighbor5) +
int(neighbor6 | neighbor7);
int N2 = int(neighbor1 | neighbor2) +
int(neighbor3 | neighbor4) +
int(neighbor5 | neighbor6) +
int(neighbor7 | neighbor0);
int N = min(N1,N2);
if ((N == 2) || (N == 3)) {
/// calculate criteria 3
int c3 = ( neighbor1 | neighbor2 | ~neighbor4) & neighbor3;
if(c3 == 0) {
pDst.at( i, j) = 0.0f;
}
}
}
}
}
}
}
void ThinSubiteration2(Mat & pSrc, Mat & pDst) {
int rows = pSrc.rows;
int cols = pSrc.cols;
pSrc.copyTo( pDst);
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
if (pSrc.at( i, j) == 1.0f) {
/// get 8 neighbors
/// calculate C(p)
int neighbor0 = (int) pSrc.at( i-1, j-1);
int neighbor1 = (int) pSrc.at( i-1, j);
int neighbor2 = (int) pSrc.at( i-1, j+1);
int neighbor3 = (int) pSrc.at( i, j+1);
int neighbor4 = (int) pSrc.at( i+1, j+1);
int neighbor5 = (int) pSrc.at( i+1, j);
int neighbor6 = (int) pSrc.at( i+1, j-1);
int neighbor7 = (int) pSrc.at( i, j-1);
int C = int(~neighbor1 & ( neighbor2 | neighbor3)) +
int(~neighbor3 & ( neighbor4 | neighbor5)) +
int(~neighbor5 & ( neighbor6 | neighbor7)) +
int(~neighbor7 & ( neighbor0 | neighbor1));
if(C == 1) {
/// calculate N
int N1 = int(neighbor0 | neighbor1) +
int(neighbor2 | neighbor3) +
int(neighbor4 | neighbor5) +
int(neighbor6 | neighbor7);
int N2 = int(neighbor1 | neighbor2) +
int(neighbor3 | neighbor4) +
int(neighbor5 | neighbor6) +
int(neighbor7 | neighbor0);
int N = min(N1,N2);
if((N == 2) || (N == 3)) {
int E = (neighbor5 | neighbor6 | ~neighbor0) & neighbor7;
if(E == 0) {
pDst.at(i, j) = 0.0f;
}
}
}
}
}
}
}
void normalizeLetter(Mat & inputarray, Mat & outputarray) {
bool bDone = false;
int rows = inputarray.rows;
int cols = inputarray.cols;
inputarray.convertTo(inputarray,CV_32FC1);
inputarray.copyTo(outputarray);
outputarray.convertTo(outputarray,CV_32FC1);
/// pad source
Mat p_enlarged_src = Mat(rows + 2, cols + 2, CV_32FC1);
for(int i = 0; i < (rows+2); i++) {
p_enlarged_src.at(i, 0) = 0.0f;
p_enlarged_src.at( i, cols+1) = 0.0f;
}
for(int j = 0; j < (cols+2); j++) {
p_enlarged_src.at(0, j) = 0.0f;
p_enlarged_src.at(rows+1, j) = 0.0f;
}
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
if (inputarray.at(i, j) >= threshold_value) { //调参
p_enlarged_src.at( i+1, j+1) = 1.0f;
}
else
p_enlarged_src.at( i+1, j+1) = 0.0f;
}
}
/// start to thin
Mat p_thinMat1 = Mat::zeros(rows + 2, cols + 2, CV_32FC1);
Mat p_thinMat2 = Mat::zeros(rows + 2, cols + 2, CV_32FC1);
Mat p_cmp = Mat::zeros(rows + 2, cols + 2, CV_8UC1);
while (bDone != true) {
/// sub-iteration 1
ThinSubiteration1(p_enlarged_src, p_thinMat1);
/// sub-iteration 2
ThinSubiteration2(p_thinMat1, p_thinMat2);
/// compare
compare(p_enlarged_src, p_thinMat2, p_cmp, CV_CMP_EQ); //比较输入的src1和src2中的元素，真为255，否则为0
/// check
int num_non_zero = countNonZero(p_cmp); //返回灰度值不为0的像素数
if(num_non_zero == (rows + 2) * (cols + 2)) {
bDone = true;
}
/// copy
p_thinMat2.copyTo(p_enlarged_src);
}
// copy result
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
outputarray.at( i, j) = p_enlarged_src.at( i+1, j+1);
}
}
}
void Line_reflect(Mat & inputarray, Mat & outputarray)
{
int rows = inputarray.rows;
int cols = inputarray.cols;
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
if (inputarray.at(i, j) == 1.0f) {
outputarray.at( i, j) = 0.0f;
}
}
}
}
// 提取连通区域，并剔除小面积联通区域
void Delete_smallregions(Mat & pSrc, Mat & pDst)
{
vector> contours; //二值图像轮廓的容器
vector hierarchy; //4个int向量，分别表示后、前、父、子的索引编号
findContours(pSrc, contours, hierarchy,RETR_LIST, CHAIN_APPROX_NONE); //检测所有轮廓
vector>::iterator k; //迭代器，访问容器数据
for (k = contours.begin(); k != contours.end();) //遍历容器,设置面积因子
{
if (contourArea(*k, false) < size)
{//删除指定元素，返回指向删除元素下一个元素位置的迭代器
k = contours.erase(k);
}
else
++k;
}
//contours[i]代表第i个轮廓，contours[i].size()代表第i个轮廓上所有的像素点
for (int i = 0; i < contours.size(); i++)
{
for (int j = 0; j < contours[i].size(); j++)
{
//获取轮廓上点的坐标
Point P = Point(contours[i][j].x, contours[i][j].y);
}
drawContours(pDst, contours,i, Scalar(255), -1, 8);
}
} 具体例子
原图：
提取所需要线段图：
骨骼化：
将骨骼化的曲线段映射到原图：
