کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10361290 | 870090 | 2015 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A scale- and orientation-adaptive extension of Local Binary Patterns for texture classification
ترجمه فارسی عنوان
توسعه یک مقیاس و جهت گیری سازگار از الگوهای محلی باینری برای طبقه بندی بافت
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Local Binary Patterns (LBPs) have been used in a wide range of texture classification scenarios and have proven to provide a highly discriminative feature representation. A major limitation of LBP is its sensitivity to affine transformations. In this work, we present a scale- and rotation-invariant computation of LBP. Rotation-invariance is achieved by explicit alignment of features at the extraction level, using a robust estimate of global orientation. Scale-adapted features are computed in reference to the estimated scale of an image, based on the distribution of scale normalized Laplacian responses in a scale-space representation. Intrinsic-scale-adaption is performed to compute features, independent of the intrinsic texture scale, leading to a significantly increased discriminative power for a large amount of texture classes. In a final step, the rotation- and scale-invariant features are combined in a multi-resolution representation, which improves the classification accuracy in texture classification scenarios with scaling and rotation significantly.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 48, Issue 8, August 2015, Pages 2633-2644
Journal: Pattern Recognition - Volume 48, Issue 8, August 2015, Pages 2633-2644
نویسندگان
Sebastian Hegenbart, Andreas Uhl,