The DOI matches its Crossref record.
An efficient differential box-counting approach to compute fractal dimension of image
Abstract
Fractal dimension is an interesting feature proposed to characterize roughness and self-similarity in a picture. This feature has been used in texture segmentation and classification, shape analysis and other problems. An efficient differential box-counting approach to estimate fractal dimension is proposed in this note. By comparison with four other methods, it has been shown that the authors, method is both efficient and accurate. Practical results on artificial and natural textured images are presented.>
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Citations
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Metadata
- Authors
- Sarkar, N., & Chaudhuri, B. B.
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics
- Published
- 1994
- Volume
- 24
- Issue
- 1
- Pages
- 115-120
- ISSN
- 0018-9472 (ISSN-L)
- OpenAlex
- W2161522250
- Cited by
- 886
- References
- 0
- FWCI
- 3.71
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: An efficient differential box-counting approach to compute fractal dimension of image. https://app.cochat.ai/papers/10.1109/21.259692
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- Sarkar, N., & Chaudhuri, B. B. (1994). An efficient differential box-counting approach to compute fractal dimension of image. IEEE Transactions on Systems, Man, and Cybernetics. https://doi.org/10.1109/21.259692
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