Statistical and structural approaches to texture

R.M. Haralick · Proceedings of the IEEE · 1979

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R.M. Haralick

Publisher

Proceedings of the IEEE

Year

1979

Language

English

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In this survey we review the image processing literature on the various approaches and models investigators have used for texture. These include statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models. We discuss and generalize some structural approaches to texture based on more complex primitives than gray tone. We conclude with some structural-statistical generalizations which apply the statistical techniques to the structural primitives.

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APA 7

Haralick, R. (1979). Statistical and structural approaches to texture. https://doi.org/10.1109/proc.1979.11328

MLA

Haralick, R.M. "Statistical and structural approaches to texture." 1979. https://doi.org/10.1109/proc.1979.11328.

Chicago

Haralick, R.M. 1979. "Statistical and structural approaches to texture.". https://doi.org/10.1109/proc.1979.11328.

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Haralick, R. 1979, Statistical and structural approaches to texture, Proceedings of the IEEE, available at: https://doi.org/10.1109/proc.1979.11328 [Accessed 8 Aug. 2026].

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Title: Statistical and structural approaches to texture

Author / contributors: R.M. Haralick

Publisher: Proceedings of the IEEE

Publication year: 1979

Language: English

Subjects

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Autocorrelation; Autoregressive model; Computer science; Artificial intelligence; Statistical model; Pattern recognition (psychology); Texture (cosmology); Texture synthesis; Image (mathematics); Algorithm; Image processing; Image texture