期刊
JOURNAL OF MICROSCOPY
卷 239, 期 2, 页码 159-166出版社
WILEY
DOI: 10.1111/j.1365-2818.2010.03365.x
关键词
Mathematical morphology; rough surfaces; statistical learning; texture classification
类别
资金
- Siemens VAI MT SAS (France)
P>A classification method based on textural information for metallic surfaces displaying complex random patterns is proposed. Because these kinds of textures show fluctuations at a small scale and some uniformity at a larger scale, a probabilistic approach is followed, considering textural variations as realizations of random functions. Taking into account information of pixel neighbourhoods, the texture for each pixel is described at different scales. By means of statistical learning, the most relevant textural descriptors are selected for each application. The performance of this approach is established on a real data set of steel surfaces.
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