Is it possible to find the edge of a "spotty" region in emgucv?
I have an image that looks like this:
and I want to find the edges of the dark part so like this (the red lines are what I am looking for):
I have tried a few approaches and none have worked so I am hoping there is an emgu guru out there willing to help me...
Approach 1
Code for this (I know that I should be disposing of things properly but I am keeping the code short):
var orig = new Image<Bgr, byte>(inFile);
var contours = orig
.Convert<Gray, byte>()
.PyrDown()
.PyrUp()
.Not()
.InRange(new Gray(190), new Gray(255))
.Canny(new Gray(190), new Gray(255))
.FindContours(CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
RETR_TYPE.CV_RETR_TREE);
var output = new Image<Gray, byte>(orig.Size);
for (; contours != null; contours = contours.HNext)
{
var poly = contours.ApproxPoly(contours.Perimeter*0.05,
contours.Storage);
output.Draw(poly, new Gray(255), 1);
}
output.Save(outFile);
This is the result:
Approach 2
Code for this:
var orig = new Image<Bgr, byte>(inFile);
var linesegs = orig
.Convert<Gray, byte>()
.PyrDown()
.PyrUp()
.Not()
.InRange(new Gray(190), new Gray(255))
.Canny(new Gray(190), new Gray(255))
.HoughLinesBinary(
1,
Math.PI/45.0,
20,
30,
10
)[0];
var output = new Image<Gray, byte>(orig.Size);
foreach (var l in linesegs)
{
output.Draw(l, new Gray(255), 1);
}
output.Save(outFile);
This is the result:
Notes
I have tried adjusting all the parameters on those two approaches and adding smoothing but I can never get the simple edges that I need because, I suppose, the darker region is not a solid colour.
I have also tried dilating and eroding but the parameters I have to put in for those are so high to get a single colour that I end up including some of the grey stuff on the right and lose accuracy.
Yes, it's possible , and here is how you could do it:
At this point you'll have the result you were looking for. For testing purposes, at the end I execute the bounding box technique to show how to detect the beggining and the end of the area of interest:
I didn't have the time to tweak the parameters and make a perfect detection, but I'm sure you can figure it out. This answer provides a roadmap for achieving that!
This is the C++ code I came up with, I trust you are capable of converting it to C#:
#include <cv.h>
#include <highgui.h>
int main(int argc, char* argv[])
{
cv::Mat image = cv::imread(argv[1]);
cv::Mat new_image = cv::Mat::zeros(image.size(), image.type());
/* Change contrast: new_image(i,j) = alpha*image(i,j) + beta */
double alpha = 1.8; // [1.0-3.0]
int beta = 100; // [0-100]
for (int y = 0; y < image.rows; y++)
{
for (int x = 0; x < image.cols; x++)
{
for (int c = 0; c < 3; c++)
{
new_image.at<cv::Vec3b>(y,x)[c] =
cv::saturate_cast<uchar>(alpha * (image.at<cv::Vec3b>(y,x)[c]) + beta);
}
}
}
cv::imshow("contrast", new_image);
/* Convert RGB Mat into HSV color space */
cv::Mat hsv;
cv::cvtColor(new_image, hsv, CV_BGR2HSV);
std::vector<cv::Mat> v;
cv::split(hsv,v);
// Perform threshold on the S channel of hSv
int thres = 15;
cv::threshold(v[1], v[1], thres, 255, cv::THRESH_BINARY_INV);
cv::imshow("saturation", v[1]);
/* Erode & Dilate */
int erosion_size = 6;
cv::Mat element = cv::getStructuringElement(cv::MORPH_CROSS,
cv::Size(2 * erosion_size + 1, 2 * erosion_size + 1),
cv::Point(erosion_size, erosion_size) );
cv::erode(v[1], v[1], element);
cv::dilate(v[1], v[1], element);
cv::imshow("binary", v[1]);
/* Bounding box */
// Invert colors
cv::bitwise_not(v[1], v[1]);
// Store the set of points in the image before assembling the bounding box
std::vector<cv::Point> points;
cv::Mat_<uchar>::iterator it = v[1].begin<uchar>();
cv::Mat_<uchar>::iterator end = v[1].end<uchar>();
for (; it != end; ++it)
{
if (*it) points.push_back(it.pos());
}
// Compute minimal bounding box
cv::RotatedRect box = cv::minAreaRect(cv::Mat(points));
// Draw bounding box in the original image (debug purposes)
cv::Point2f vertices[4];
box.points(vertices);
for (int i = 0; i < 4; ++i)
{
cv::line(image, vertices[i], vertices[(i + 1) % 4], cv::Scalar(0, 255, 0), 2, CV_AA);
}
cv::imshow("box", image);
cvWaitKey(0);
return 0;
}