Parsing Intensity Profiles,
CGIP(6), No. 1, February 1977, pp. 43-60.
Elsevier DOI PROPAR, analysis of 1-D profiles. BibRef 7702
Rationalizing Edge Detectors,
CGIP(8), No. 2, October 1978, pp. 277-285.
Elsevier DOI Analysis of early operators like Roberts (
See also Machine Perception of 3-D Solids. ) and Prewitt (
See also Object Enhancement and Extraction. ). BibRef 7810
The Geometry of Differential Operators with Application to Image Processing,
PAMI(11), No. 12, December 1989, pp. 1252-1264.
IEEE DOI Discuss a family of differential operators that can be used to build edge detectors such as that of Canny. BibRef 8912
The Local Structure of Image Discontinuities in One Dimension,
PAMI(9), No. 3, May 1987, pp. 341-355. BibRef 8705
Earlier: ICPR84(46-48). Over kill on the 1-D edge case. Maybe if the method is expanded to 2-D there can be something here. For 2-d:
See also Capturing the Local Structure of Image Discontinuities in Two Dimensions. BibRef
The Local Structure of Image Intensity Discontinuities,
Ph.D.Thesis, McGill University, Montréal, Québec, Canada, May 1989. BibRef 8905
On Edge Detection,
PAMI(8), No. 2, March 1986, pp. 147-163. BibRef 8603
Earlier: MIT AI Memo-768, August 1984. Billed as the first of "many" papers on edge detection. Analysis of 5 edge detectors --
See also Binford-Horn Line Finder, The.
See also Optimal Frequency Domain Filter for Edge Detection in Digital Pictures, An.
See also Theory of Edge Detection.
See also Edge and Region Analysis for Digital Image Data. and
See also Computational Approach to Edge Detection, A. BibRef
Directional Selectivity and its Use in Early Visual Processing,
RoyalP(B-211), 1981, pp. 151-180. BibRef 8100
Earlier: MIT AI Memo-524, June 1979. Edges, History. One of the edge detection papers.
See also Early Processing of Visual Information. BibRef
The Low-level Symbolic Representation of Intensity Changes in an Image,
MIT AI Memo-325, December 1974.
WWW Link. BibRef 7412
The Recognition of Sharp, Closely Spaced Edges,
MIT AI Memo-326, December 1974.
WWW Link. BibRef 7412
Visual Information Processing: The Structure and Creation of Visual Representations,
Royal(B-290), 1980, pp. 199-218. BibRef 8000
Edge-Detection Algorithm and Its Video-Rate Implementation,
IVC(5), No. 2, May 1987, pp. 155-160.
Elsevier DOI BibRef 8705
Efficient Approach for the Detection of Diffuse Edges,
OptEng(35), No. 12, December 1996, pp. 3522-3530. 9701
Jain, A.K.[Anil K.],
Lambda-Tau-Space Representation of Images and Generalized Edge Detector,
PAMI(19), No. 6, June 1997, pp. 545-563.
IEEE DOI 9708
IEEE DOI Scale Space. Tau is the shape of the detector, Lambda is the size. This formulation encompasses many existing detectors. Generate a class of detectors by changing the two variables. BibRef
Two dimensional generalized edge detector,
IEEE DOI 9909
The 'independent components' of natural scenes are edge filters,
Vision Research(37), No. 23, 1997, pp. 3327. BibRef 9700
Li, F.W.B.[Frederick W. B.],
DOOBNet: Deep Object Occlusion Boundary Detection from an Image,
Springer DOI 1906
Occlusion Boundaries: Low-Level Detection to High-Level Reasoning,
CMU-RI-TR-08-06, May, 2008. BibRef 0805 Ph.D.Thesis, May, 2008.
WWW Link. BibRef
Edge and line detection as exercises in hypothesis testing,
IEEE DOI 0505
Plataniotis, K.N.[Konstantinos N.],
Subjective analysis of edge detectors in color image processing,
Springer DOI 9709
Occlusion Detection in Early Vision,
IEEE DOI BibRef 9000
Chapter on Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform continues in
Basic Edges, Gradient Computations .