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المجالالرؤية الحاسوبيةالرؤية الحاسوبية
العائلةMachine learningMachine learning
سنة النشأة19831986
صاحب الطريقةAndrew Witkin and Tony LindebergJohn Canny
النوعTheoretical framework for multi-scale processingImage gradient analysis
المصدر التأسيسيLindeberg, T. (1994). Scale-space theory: A basic tool for analyzing structures at different scales. Journal of Applied Statistics, 21(2), 225–270. DOI ↗Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), 679–698. DOI ↗
الأسماء البديلةMulti-scale analysis, Gaussian scale-spaceCanny operator, Canny edge detector
ذات صلة55
الملخصScale-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.
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ScholarGateقارن الطرق: Scale-Space Theory · Canny Edge Detection. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare