@inProceedings{
 title = {Texture classification by multi-predicate Local Binary Pattern operators.},
 type = {inProceedings},
 year = {2000},
 id = {cc96d833-8223-3bd9-a0b1-7e3cd9dd1be9},
 created = {2019-11-19T13:01:29.953Z},
 file_attached = {false},
 profile_id = {bddcf02d-403b-3b06-9def-6d15cc293e20},
 group_id = {17585b85-df99-3a34-98c2-c73e593397d7},
 last_modified = {2019-11-19T13:45:22.379Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {mvg:1},
 source_type = {inproceedings},
 notes = {Proc. 15th International Conference on Pattern Recognition, Barcelona, Spain, 3:951 - 954.},
 private_publication = {false},
 abstract = {This paper benchmarks the simple Local Binary Pattern (LBP) approach in the supervised texture segmentation problems of the recent comparative study of Randen and Husøy. A multi-predicate version of LBP is proposed, making our approach even more powerful for images containing textures at multiple scales.},
 bibtype = {inProceedings},
 author = {Mäenpää T, Pietikäinen M & Ojala T}
}

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