So sánh phương pháp

	Lý thuyết không gian tỷ lệ	Phát hiện biên Canny
Lĩnh vực	Thị giác máy tính	Thị giác máy tính
Họ	Machine learning	Machine learning
Năm ra đời	1983	1986
Người khởi xướng	Andrew Witkin and Tony Lindeberg	John Canny
Loại	Theoretical framework for multi-scale processing	Image gradient analysis
Công trình gốc	Lindeberg, T. (1994). Scale-space theory: A basic tool for analyzing structures at different scales. Journal of Applied Statistics, 21(2), 225–270.	Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), 679–698.
Tên gọi khác	Multi-scale analysis, Gaussian scale-space	Canny operator, Canny edge detector
Liên quan	5	5
Tóm tắt	Scale-space theory, developed by Witkin and Lindeberg, provides a principled mathematical framework for analyzing images at multiple scales simultaneously. By treating scale as an explicit dimension and using Gaussian blurring, scale-space theory enables detection and analysis of features at appropriate scales, solving the fundamental problem of 'which scale should I analyze at?'	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.