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Cited by 280

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

The Topographic Primal Sketch

Haralick, Robert M., Watson, Layne T., Laffey, Thomas J.·1983·The International Journal of Robotics Research

Abstract

A complete mathematical treatment is given for describing the topographic primal sketch of the underlying gray tone intensity surface of a digital image. Each picture element is independently classified and assigned a unique descriptive label, invariant under monotonically increasing gray tone transformations from the set ( peak, pit, ridge, ravine, saddle, flat, and hillside), with hillside having subcategories ( inflection point, slope, convex hill, concave hill, and saddle hill). The topographic classification is based on the first and second directional derivatives of the estimated image- intensity surface. A local, facet model, two-dimensional, cubic polynomial fit is done to estimate the image-intensity surface. Zero-crossings of the first directional derivative are identified as locations of interest in the image.

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Crossref · 10.1177/027836498300200105

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Metadata

Authors
Haralick, R. M., Watson, L. T., & Laffey, T. J.
Venue
The International Journal of Robotics Research
Published
1983-03
Volume
2
Issue
1
Pages
50-72
ISSN
  • 0278-3649 (ISSN-L)
  • 1741-3176
OpenAlex
W2000367729
Cited by
280
References
4
FWCI
12.18
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Topographic Primal Sketch. https://app.cochat.ai/papers/10.1177/027836498300200105
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Haralick, R. M., Watson, L. T., & Laffey, T. J. (1983). The Topographic Primal Sketch. The International Journal of Robotics Research. https://doi.org/10.1177/027836498300200105

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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.