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Rapid Texture Identification:
Abstract
A method is presented for classifying each pixel of a textured image, and thus for segmenting the scene. The "texture energy" approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation. Normalization by the local mean and standard deviation eliminates the need for histogram equalization. Rotation-invariance can also be achieved by using averages of the texture energy features. The convolution masks are separable, and can be implemented with 1-dimensional (vertical and horizontal) or multipass 3x3 convolutions. Special techniques permit rapid processing on general-purpose digital computers.
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Cited by
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Predicting cancer outcomes with radiomics and artificial intelligence in radiology
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Arivazhagan, S., & Ganesan, L. (2003) · Pattern Recognition Letters · doi:10.1016/s0167-8655(02)00390-2 · Cited by 506
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Metadata
- Authors
- Laws, K. I.
- Venue
- SPIE Proceedings
- Publisher
- SPIE
- Published
- 1980-12-23
- Volume
- 0238
- Pages
- 376-381
- ISSN
- 0277-786X (ISSN-L)
- OpenAlex
- W2107167693
- Cited by
- 545
- References
- 0
- FWCI
- 1.79
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Laws, K. I. (1980). Rapid Texture Identification:. SPIE Proceedings. https://doi.org/10.1117/12.959169
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