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Cited by 377

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Edge detection with embedded confidence

Meer, P., Georgescu, B.·2001·IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

Computing the weighted average of the pixel values in a window is a basic module in many computer vision operators. The process is reformulated in a linear vector space and the role of the different subspaces is emphasized. Within this framework wellknown artifacts of the gradient-based edge detectors, such as large spurious responses can be explained quantitatively. It is also shown that template matching with a template derived from the input data is meaningful since it provides an independent measure of confidence in the presence of the employed edge model. The widely used three-step edge detection procedure - gradient estimation, non-maxima suppression, hysteresis thresholding - is generalized to include the information provided by the confidence measure. The additional amount of computation is minimal and experiments with several standard test images show the ability of the new procedure to detect weak edges.

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Metadata

Authors
Meer, P., & Georgescu, B.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Published
2001
Volume
23
Issue
12
Pages
1351-1365
ISSN
0162-8828 (ISSN-L)
OpenAlex
W2122069218
Cited by
377
References
20
FWCI
9.74
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Edge detection with embedded confidence. https://app.cochat.ai/papers/10.1109/34.977560
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Meer, P., & Georgescu, B. (2001). Edge detection with embedded confidence. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.977560

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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