Edge detection after the image processing-CodePudding

Consult, in the process of image processing, use soble or canny operator detects irregular edge profile, as the closed loop, how will all points within the contour in the original image is set to 0 or 255, is to how to get to the limit in the original image to change the location of the ah,

CodePudding user response:

Has been resolved, you can use the area fill, in the designated area for inflation, has a direct use of matlab functions, such as bwfill,

CodePudding user response:

Are you sure is a closed loop, use findcontours outline, reoccupy drawcontours fill contour, finally will fill the figure with the original mask

CodePudding user response:

refer to the second floor zhangli00 response:

are you sure is a closed loop, with findcontours outline, reoccupy drawcontours fill contour, finally will fill the figure with the original mask

This is a good solution

CodePudding user response:

Fyi:

 # include "opencv2/highgui/highgui. HPP" 
# include "opencv2/imgproc/imgproc HPP" 
# include "opencv2/imgproc/imgproc_c. H" 
using namespace std; 
Using the namespace CV; 
Mat img, smallImg, gray, bw; 
VectorVector Contours. 
Int threshval=128; 
The Rect r; 
The Rect maxrect brect; 
Int independence idx, n; 
Const static Scalar colors [15]={
CV_RGB (0, 0128), 
CV_RGB (0128, 0), 
CV_RGB (0128128), 
CV_RGB (128, 0, 0), 
CV_RGB (128, 0128), 
CV_RGB (128128, 0), 
CV_RGB (128128128), 
CV_RGB (160160160), 
CV_RGB (0, 0255), 
CV_RGB (0255, 0), 
CV_RGB (0255255), 
CV_RGB (255, 0, 0), 
CV_RGB (255, 0255), 
CV_RGB (255255, 0), 
CV_RGB (255255255), 
}; 
Scalar color; 
Void gamma_correct (Mat& Img, Mat& DST, double gamma) {
Mat temp. 
CvMat TMP. 

Img. ConvertTo (temp, CV_32FC1, 1.0/255.0, 0.0); 
TMP=temp; 
CvPow (& amp; TMP, & amp; TMP, gamma); 
Temp. ConvertTo (DST, CV_8UC1, 255.0, 0.0); 
} 
Int main () {
CvNamedWindow (" display ", 1); 
Img=imread (" image. JPG ", 1); 
R.x=img. Cols/10; 
R.y=img. Rows/3; 
Truly idth=img. Cols * 8/10; 
R.h. eight=img. Rows * 2/3; 
SmallImg=img (r); 
CvtColor (smallImg, gray, CV_BGR2GRAY); 
//medianBlur (gray, gray, 5); 
EqualizeHist (gray, gray); 
Gamma_correct (gray, gray, 4.0); 
Imshow (" display ", gray); 
waitKey(0); 

Bw=(gray> Threshval); 
Imshow (" display ", bw); 
waitKey(0); 

Mat Structure0=getStructuringElement (MORPH_RECT, Size (3, 3)); 
Erode (bw, bw, Structure0, Point (1, 1)); 
Mat Structure1=getStructuringElement (MORPH_RECT, Size (6, 6)); 
Dilate (bw, bw, Structure1, Point (1, 1)); 
Imshow (" display ", bw); 
waitKey(0); 

FindContours (bw, contours, hierarchy, RETR_EXTERNAL CHAIN_APPROX_SIMPLE); 
if (! Contours. The empty () & amp; & ! Hierarchy. The empty ()) {
Independence idx=0; 
N=0; 
Vector Approx. 
for (; Idx>=0; Independence idx=hierarchy [independence idx] [0]) {
Color=colors [15] independence idx %; 
//drawContours (smallImg, contours, independence idx, color, and 1, 8, hierarchy); 
ApproxPolyDP (Mat (contours [independence idx]), approx, arcLength (Mat (contours [independence idx]), true) * 0.005, true);//0.005 will flash straightening coefficient 
Const Point * p=& amp; Approx [0]. 
Int m=(int) approx. The size (); 
Polylines (smallImg, & amp; P, & amp; M, 1, true, color); 
Circle (smallImg, Point (p [0]. X, p [0]. Y), 3, color); 
Circle (smallImg, Point (p [1]. X, p [1]. Y), 2, color); 
For (int I=2; iN++; 
If (1==n) {
Maxrect=boundingRect (Mat (contours [independence idx])); 
} else {
Brect=boundingRect (Mat (contours [independence idx])); 
CvRect Mr (maxrect), br (brect); 
Maxrect=cvMaxRect (& amp; Mr, & amp; Br); 
} 
} 
Circle (smallImg, Point (maxrect. X + maxrect. Width/2, maxrect. Y + maxrect. Height/2), 2, CV_RGB (0, 255)); 
} 
Imshow (" display ", smallImg); 
waitKey(0); 
CvDestroyWindow (" display "); 
Return 0; 
}