In computer vision and image processing, edge detection concerns the localization of significant variations of the grey level image and the identification of the physical phenomena that originated them. This information is very useful for applications in 3D reconstruction, motion, recognition, image enhancement and restoration, image registration, image compression, and so on. Usually, edge detection requires smoothing and differentiation of the image. Differentiation is an ill-conditioned problem and smoothing results in a loss of information. It is difficult to design a general edge detection algorithm which performs well in many contexts and captures the requirements of subsequent processing stages. Consequently, over the history of digital image processing a variety of edge detectors have been devised which differ in their mathematical and algorithmic properties. This paper is an account of the current state of our understanding of edge detection. We propose an overview of research in edge detection: edge definition, properties of detectors, the methodology of edge detection, the mutual influence between edges and detectors, and
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1662
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A computational approach to edge detection
– Canny
- 1986
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658
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Scale-space and edge detection using anisotropic diffusion
– Perona, Malik
- 1990
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548
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Theory of edge detection
– Marr, Hildreth
- 1980
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531
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The design and use of steerable filters
– Freeman, Adelson
- 1991
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392
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Scale-space filtering
– Witkin
- 1983
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155
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Using canny's criteria to derive a recursively implemented optimal edge detector
– Deriche
- 1987
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132
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On edge detection
– Torre, Poggio
- 1986
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120
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Edge Detection and Ridge Detection with Automatic Scale Selection
– Lindeberg
- 1998
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114
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Scaling theorems for zero crossing
– Yuille, Poggio
- 1986
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113
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Uniqueness of the Gaussian kernel for scalespace filtering
– Babaud, Witkin, et al.
- 1986
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107
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Finding edges and lines in images
– Canny
- 1993
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100
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Digital step edges from zero crossing of second directional derivatives
– Haralick
- 1984
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91
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A Guided Tour of Computer Vision
– Nalwa
- 1993
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83
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A Computational approach for corner and vertex detection
– Deriche, Giraudon
- 1993
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73
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Edge focusing
– Bergholm
- 1987
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69
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Feature detection from local energy
– Morrone, Owens
- 1987
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67
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Fast Algorithms for Low-Level Vision
– Deriche
- 1990
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67
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Detection of roads and linear structures in low resolution aerial imagery using a multisource knowledge integration technique
– Fischler, Tenenbaum, et al.
- 1981
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62
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Detecting and Localizing Edges Composed of Steps, Peaks, and Roofs
– Perona, Malik
- 1990
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61
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Parametric feature detection
– Baker, Nayar, et al.
- 1998
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58
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On detecting edges
– Nalwa, Binford
- 1986
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52
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Edge and Curve Detection for Visual Scene analysis
– Rosenfeld, Thurston
- 1971
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51
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A realistic camera model for computer graphics
– Kolb, Mitchell, et al.
- 1995
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49
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Finding corners
– Noble
- 1988
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47
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A survey of edge detection techniques
– Davis
- 1976
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44
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Object enhancement and extraction
– Prewitt
- 1970
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41
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Recognizing corners by fitting parametric models
– Rohr
- 1992
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41
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An Optimal Linear Operator for Step Edge Detection
– Shen, Castan
- 1992
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37
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An Operator Which Locates Edges in Digitized Pictures
– Hueckel
- 1971
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36
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Recovering and Characterizing Image Features Using An Efficient Model Based Approach
– Deriche, Blaszka
- 1993
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33
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Optimal edge detection using recursive filtering
– Deriche
- 1987
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31
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Ill-posed Problems and Regularization Analysis in Early Vision
– Poggio, Torre
- 1984
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30
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Optimal edge detectors for ramp edges
– Petrou, Kittler
- 1991
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28
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Expert systems for image processing: knowledge-based composition of image analysis processes
– Matsuyama
- 1989
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26
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A Regularized Solution to Edge Detection
– Poggio, Voorhees, et al.
- 1988
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26
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On Optimal Infinite Impulse Response Edge Detection Filters
– Sarkar, Boyer
- 1991
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24
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Authenticating edges produced by zero-crossing algorithms
– Clark
- 1989
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24
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Early Jump-Out Corner Detectors
– Cooper, Venkatesh, et al.
- 1993
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23
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The Detection of Intensity Changes by Computer and Biological Vision Systems
– Hildreth
- 1983
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23
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F.: Toward a symbolic representation of intensity changes in images
– Korn
- 1988
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23
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Discrete derivative approximations with scale-space properties: a basis for low-level feature extraction
– Lindeberg
- 1993
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22
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Accuracy of Laplacian Edge Detectors
– Berzins
- 1984
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21
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A Local Visual Operator Which Recognizes Edges and Lines
– Hueckel
- 1973
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21
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Toward a Surface Primal Sketch
– Ponct, Brady
- 1985
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21
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Edge detection and motion detection
– Spacek
- 1986
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20
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Detection of intensity changes with subpixel accuracy using Laplacian-gaussian masks
– Huertas, Medioni
- 1986
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20
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A Methodology for Quantitative Performance Evaluation of Detection Algorithms
– Kanungo, Jaisimha, et al.
- 1995
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19
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Reasoning about Edges in Scale Space
– Lu, Jain
- 1992
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19
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On the classification of image features
– Venkatesh, Owens
- 1990
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18
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di Baja. A Width-Independent Fast Thinning Algorithm
– Arcelli, Sanniti
- 1985
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