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 | Detect Polygons in an Image using OpenCV
- Python Program to detect the edges of an image using OpenCV | Sobel edge detection method
- Python | Corner Detection with Shi-Tomasi Corner Detection Method using OpenCV
- Python | Corner detection with Harris Corner Detection method using OpenCV
- Detect an object with OpenCV-Python
- Log transformation of an image using Python and OpenCV
- Image Translation using OpenCV | Python
- Image Pyramid using OpenCV | Python
- Image Resizing using OpenCV | Python
- Reading an image in OpenCV using Python
- Image Processing without OpenCV | Python
- Python | Image blurring using OpenCV
- Image Steganography using OpenCV in Python
- Cartooning an Image using OpenCV - Python
- Image Registration using OpenCV | Python
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. 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.