کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969314 1449931 2017 25 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
High-dimensional feature extraction using bit-plane decomposition of local binary patterns for robust face recognition
ترجمه فارسی عنوان
استخراج ویژگی های با ابعاد بزرگ با استفاده از تقسیم بیتی از الگوی باینری محلی برای تشخیص چهره قوی
کلمات کلیدی
تشخیص چهره، استخراج ویژگی، الگوی دودویی محلی، ویژگی بسیار بالا، تجزیه و تحلیل خطی خطی، تجزیه بیت-هواپیما،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Transforming an original image into a high-dimensional (HD) feature has been proven to be effective in classifying images. This paper presents a novel feature extraction method utilizing the HD feature space to improve the discriminative ability for face recognition. We observed that the local binary pattern can be decomposed into bit-planes, each of which has scale-specific directional information of the face image. Each bit-plane not only has the inherent local-structure of the face image but also has an illumination-robust characteristic. By concatenating all the decomposed bit-planes, we generate an HD feature vector with an improved discriminative ability. To reduce the computational complexity while preserving the incorporated local structural information, a supervised dimension reduction method, the orthogonal linear discriminant analysis, is applied to the HD feature vector. Extensive experimental results show that existing classifiers with the proposed feature outperform those with other conventional features under various illumination, pose, and expression variations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 45, May 2017, Pages 11-19
نویسندگان
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