選擇輪廓(select_shape)
Halcon是一款運用廣泛的圖像識别和處理軟體。在膚淺的接觸中，它的輪廓選擇算子(select_shape)給予我很深的印象。結果是往往幾行代碼就能夠産生很好的效果：
比如要得到這樣的結果
隻需要
read_image (Image1, 'F:/未來項目/鋼管識别/FindTube/FindTube/1.jpg')
rgb1_to_gray (Image1, GrayImage)
threshold (GrayImage, Regions, 43, 111)
connection (Regions, ConnectedRegions)
select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 150, 666)
select_shape (SelectedRegions, SelectedRegions1, 'circularity', 'and', 0.45, 1)
當然Halcon是在背後做了許多工作的。
幾行代碼中，比較重要的是算子就是"select_shape"。這個算子的參數很多，我也就比較熟悉這兩種。
如果我想在Opencv中也要這樣的結果，就需要自己動手嘗試實作。實作過程中我采用了類似的函數名表示敬意。
// selectshape.cpp : 選擇輪廓
// by: jsxyhelu(1755311380)
#include "stdafx.h"
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
using namespace std;
using namespace cv;
#define VP vector<Point> //用VP符号代替 vector<point>
RNG rng(12345 );
//帶有上下限的threshold
void threshold2(Mat gray,Mat& thresh,int minvalue,int maxvalue)
{
Mat thresh1;
Mat thresh2;
threshold(gray,thresh1,43,255, THRESH_BINARY);
threshold(gray,thresh2,111,255,THRESH_BINARY_INV);
thresh = thresh1 & thresh2;
}
//尋找并繪制出聯通區域
vector<VP> connection2(Mat src,Mat& draw)
{
draw = Mat::zeros(src.rows,src.cols,CV_8UC3);
vector<VP>contours;
findContours(src,contours,CV_RETR_LIST,CV_CHAIN_APPROX_SIMPLE);
for (int i=0;i<contours.size();i++)
{
Scalar color = Scalar(rng.uniform(0,255),rng.uniform(0,255),rng.uniform(0,255));
drawContours(draw,contours,i,color,-1);
}
return contours;
//select_shape
vector<VP> selectShapeArea(Mat src,Mat& draw,vector<VP> contours,int minvalue,int maxvalue)
vector<VP> result_contours;
{
int countour_area = contourArea(contours[i]);
if (countour_area >minvalue && countour_area<maxvalue)
{
result_contours.push_back(contours[i]);
}
for (int i=0;i<result_contours.size();i++)
drawContours(draw,result_contours,i,color,-1);
return result_contours;
//計算輪廓的圓的特性
float calculateCircularity(VP contour)
Point2f center;
float radius = 0;
minEnclosingCircle((Mat)contour,center,radius);
//以最小外接圓半徑作為數學期望，計算輪廓上各點到圓心距離的标準差
float fsum = 0;
float fcompare = 0;
for (int i=0;i<contour.size();i++)
{
Point2f ptmp = contour[i];
float fdistenct = sqrt((float)((ptmp.x - center.x)*(ptmp.x - center.x)+(ptmp.y - center.y)*(ptmp.y-center.y)));
float fdiff = abs(fdistenct - radius);
fsum = fsum + fdiff;
fcompare = fsum/(float)contour.size();
return fcompare;
vector<VP> selectShapeCircularity(Mat src,Mat& draw,vector<VP> contours,float minvalue,float maxvalue)
float fcompare = calculateCircularity(contours[i]);
if (fcompare >=minvalue && fcompare <=maxvalue)
int _tmain(int argc, _TCHAR* argv[])
Mat src;
Mat gray;
Mat thresh;
Mat draw_connection;
Mat draw_area;
Mat draw_circle;
vector<VP>contours_connection;
vector<VP>contours_area;
vector<VP>contours_circle;
vector<VP>contours_tmp;
//read_image (Image1, 'F:/未來項目/鋼管識别/FindTube/FindTube/1.jpg')
src = imread("1.jpg");
//rgb1_to_gray (Image1, GrayImage)
cvtColor(src,gray,COLOR_BGR2GRAY);
//threshold (GrayImage, Regions, 43, 111)
threshold2(gray,thresh,43,111);
//connection (Regions, ConnectedRegions)
contours_connection = connection2(thresh.clone(),draw_connection);
//select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 150, 666)
contours_area = selectShapeArea(thresh.clone(),draw_area,contours_connection,150,666);
//select_shape (SelectedRegions, SelectedRegions1, 'circularity', 'and', 0.45, 1)
contours_circle = selectShapeCircularity(thresh.clone(),draw_circle,contours_area,1,6);
//顯示結果
imshow("src",src);
imshow("thresh",thresh);
imshow("draw_connection",draw_connection);
imshow("draw_area",draw_area);
imshow("draw_circle",draw_circle);
waitKey();
結果如下，這段代碼中還有一個問題，就是計算輪廓圓的性質的方法，我這裡采用的是自己想出來的方法，似乎不是很完善，需要進一步找到資料才修正。
目前方向：圖像拼接融合、圖像識别
聯系方式：[email protected]