OpenCV (Open Source Computer Vision) is a computer vision library that contains various functions to perform operations on Images or videos. OpenCV library can be used to perform multiple operations on videos.
Let’s see how to detect the corner in the image.
cv2.goodFeaturesToTrack() method finds N strongest corners in the image by Shi-Tomasi method. Note that the image should be a grayscale image. Specify the number of corners you want to find and the quality level (which is a value between 0-1). It denotes the minimum quality of corner below which everyone is rejected. Then provide the minimum Euclidean distance between corners detected.
cv2.goodFeaturesToTrack(image, maxCorners, qualityLevel, minDistance[, corners[, mask[, blockSize[, useHarrisDetector[, k]]]]])
Image before corner detection:
Image after corner detection –
- Python Program to detect the edges of an image using OpenCV | Sobel edge detection method
- Python | Corner detection with Harris Corner Detection method using OpenCV
- Python | Corner Detection with Shi-Tomasi Corner Detection Method using OpenCV
- Image Processing without OpenCV | Python
- Image Translation using OpenCV | Python
- Cartooning an Image using OpenCV - Python
- Reading an image in OpenCV using Python
- Python | Image blurring using OpenCV
- Image Resizing using OpenCV | Python
- Image Registration using OpenCV | Python
- Image Pyramid using OpenCV | Python
- OpenCV Python Program to blur an image
- Find Circles and Ellipses in an Image using OpenCV | Python
- Python | OpenCV program to read and save an Image
- OpenCV Python Program to analyze an image using Histogram
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to email@example.com. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.