Machine learningEdge detection
Canny Edge Detection
The Canny edge detector, introduced by John Canny in 1986, is a multi-stage algorithm for identifying edges in digital images where significant intensity changes occur. Canny's method is optimal for step edges in additive Gaussian noise and remains the gold standard for edge detection in computer vision due to its mathematical elegance and practical effectiveness.
Open in MethodMindSoonVideoSoon
Read the full method
Members only
Sign inSign in with a free account to read this section.
Sources
- Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), 679–698. DOI: 10.1109/TPAMI.1986.4767851 ↗
- Sobel, I., & Feldman, G. (1968). A 3x3 isotropic gradient operator for image processing. Pattern Recognition and Machine Intelligence, 271–272. link ↗