The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Canny edge detection enhancement by scale multiplication
Abstract
The technique of scale multiplication is analyzed in the framework of Canny edge detection. A scale multiplication function is defined as the product of the responses of the detection filter at two scales. Edge maps are constructed as the local maxima by thresholding the scale multiplication results. The detection and localization criteria of the scale multiplication are derived. At a small loss in the detection criterion, the localization criterion can be much improved by scale multiplication. The product of the two criteria for scale multiplication is greater than that for a single scale, which leads to better edge detection performance. Experimental results are presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
A Wavelet Tour of Signal Processing
(1999) · Elsevier eBooks · doi:10.1016/b978-0-12-466606-1.x5000-4 · Cited by 16,227
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
Digital Image Processing: PIKS Scientific Inside
Pratt, W. K. (2007) · Wiley eBooks · doi:10.1002/0470097434 · Cited by 2,616
Black, M. J., Sapiro, G., Marimont, D. H., & Heeger, D. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.661192 · Cited by 1,295
Jähne, B. (1991) · Springer eBooks · doi:10.1007/978-3-662-11565-7 · Cited by 1,222
Wavelet transform domain filters: a spatially selective noise filtration technique
Xu, Y., Weaver, J. B., Healy, D. M., & Lu, J. (1994) · IEEE Transactions on Image Processing · doi:10.1109/83.336245 · Cited by 747
Digital image processing (2nd ed.)
Pratt, W. K. (1991) · John Wiley & Sons, Inc. eBooks · Cited by 380
Noise reduction for magnetic resonance images via adaptive multiscale products thresholding
Bao, P., & Zhang, L. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.816958 · Cited by 295
Self-citationMultidimensional Gaussian Distributions
Posten, H. O. (1966) · Technometrics · doi:10.1080/00401706.1966.10490364 · Cited by 263
Cited by
Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data
Sundaresan, P., Grannen, J., Thananjeyan, B., Balakrishna, A., Laskey, M., Stone, K., Gonzalez, J. E., & Goldberg, K. (2020) · 2020 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra40945.2020.9197121 · Cited by 107
A pixel-based color image segmentation using support vector machine and fuzzy -means
Wang, X.-Y., Zhang, X.-J., Yang, H.-Y., & Bu, J. (2012) · Neural Networks · doi:10.1016/j.neunet.2012.04.012 · Cited by 42
Passenger Detection and Counting for Public Transport System
Khan, S. H., Yousaf, M. H., Murtaza, F., & Velastin, S. (2020) · NED University Journal of Research · doi:10.35453/nedjr-ascn-2019-0016 · Cited by 31
Metadata
- Authors
- Bao, P., Zhang, L., & Wu, X.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2005-09
- Volume
- 27
- Issue
- 9
- Pages
- 1485-1490
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2106097225
- Cited by
- 601
- References
- 16
- FWCI
- 13.96
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Canny edge detection enhancement by scale multiplication. https://app.cochat.ai/papers/10.1109/tpami.2005.173
- The paper
- Bao, P., Zhang, L., & Wu, X. (2005). Canny edge detection enhancement by scale multiplication. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2005.173
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
