The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
On Detecting Edges
Abstract
An edge in an image corresponds to a discontinuity in the intensity surface of the underlying scene. It can be approximated by a piecewise straight curve composed of edgels, i.e., short, linear edgeelements, each characterized by a direction and a position. The approach to edgel-detection here, is to fit a series of one-dimensional surfaces to each window (kernel of the operator) and accept the surfacedescription which is adequate in the least squares sense and has the fewest parameters. (A one-dimensional surface is one which is constant along some direction.) The tanh is an adequate basis for the step-edge and its combinations are adequate for the roof-edge and the line-edge. The proposed method of step-edgel detection is robust with respect to noise; for (step-size/noise) > 2.5, it has subpixel position localization (position < 3) and an angular localization better than 100; further, it is designed to be insensitive to smooth shading. These results are demonstrated by some simple analysis, statistical data, and edgel-images. Also included is a comparison of performance on a real image, with a typical operator (Difference-of-Gaussians). The results indicate that the proposed operator is superior with respect to detection, localization, and resolution.
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Citations
Cites
Introduction to Fourier optics
Goodman, J. W. (1968) · Cited by 10,608
Marr, D., & Hildreth, E. (1980) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1980.0020 · Cited by 6,510
Yarlagadda, R. (1976) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1976.1162867 · Cited by 1,739
Digital Step Edges from Zero Crossing of Second Directional Derivatives
Haralick, R. M. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767475 · Cited by 1,026
Finding Edges and Lines in Images
Canny, J. (1983) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 833
A survey of edge detection techniques
Davis, L. S. (1975) · Computer Graphics and Image Processing · doi:10.1016/0146-664x(75)90012-x · Cited by 813
Quantitative design and evaluation of enhancement/thresholding edge detectors
Abdou, I. E., & Pratt, W. K. (1979) · Proceedings of the IEEE · doi:10.1109/proc.1979.11325 · Cited by 778
Picture processing and psychopictorics
(1971) · Icarus · doi:10.1016/0019-1035(71)90136-9 · Cited by 766
Sondhi, M. (1978) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1978.1163057 · Cited by 539
An Operator Which Locates Edges in Digitized Pictures
Hueckel, M. H. (1971) · Journal of the ACM · doi:10.1145/321623.321635 · Cited by 407
Cited by
Artificial Intelligence: A New Synthesis
(1998) · Elsevier eBooks · doi:10.1016/c2009-0-27773-7 · Cited by 1,163
Structure from stereo-a review
Dhond, U. R., & Aggarwal, J. K. (1989) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/21.44067 · Cited by 867
Bajcsy, R. (1988) · Proceedings of the IEEE · doi:10.1109/5.5968 · Cited by 830
A robust visual method for assessing the relative performance of edge-detection algorithms
Heath, M. D., Sarkar, S., Sanocki, T., & Bowyer, K. W. (1997) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.643893 · Cited by 494
Gabor filter-based edge detection
Mehrotra, R., Namuduri, K. R., & Ranganathan, N. (1992) · Pattern Recognition · doi:10.1016/0031-3203(92)90121-x · Cited by 444
Metadata
- Authors
- Nalwa, V. S., & Binford, T. O.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1986-11
- Volume
- PAMI-8
- Issue
- 6
- Pages
- 699-714
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2078085827
- Cited by
- 437
- References
- 14
- FWCI
- 18.95
- Type
- journal article
- Language
- en
- Open access
- closed
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