#dotnet – detecting corners on the 🎦 camera feed with FAST algorithm, #OpenCV and #net5

Hi !

Today is a quick one: FAST corner detection algorithm.

FAST (Features from Accelerated Segment Test) algorithm was proposed by Edward Rosten and Tom Drummond in their paper “Machine learning for high-speed corner detection” in 2006 (Later revised it in 2010). A basic summary of the algorithm is presented below. Refer original paper for more details (All the images are taken from original paper).

OpenCV includes the FAST algorithm as part of the base set of operations to perform on an image. You only need 2 lines of code to get this output.

The OpenCV FAST tutorial (see references) explain the different steps and, I’ll keep this simple, just sharing the code !

	public Mat applyEffect(Mat image)
	{
	var newImage = new Mat();
	Cv2.CvtColor(image, newImage, ColorConversionCodes.BGR2GRAY, 0);
	KeyPoint[] keypoints = Cv2.FAST(newImage, 50, true);
	foreach (KeyPoint kp in keypoints)
	newImage.Circle((Point)kp.Pt, 3, Scalar.Red, –1, LineTypes.AntiAlias, 0);
	return newImage;
	}

view raw opencvsharpnet5Fasteffect.cs hosted with ❤ by GitHub

That’s all for today!

References

• OpenCVSharp, https://github.com/shimat/opencvsharp
• Wikipedia, Canny Edge Detector
• OpenCV, Canny tutorial
• openCV, FAST tutorial
• Wikipedia, FAST