کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
408223 679010 2011 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modified locally linear discriminant embedding for plant leaf recognition
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Modified locally linear discriminant embedding for plant leaf recognition
چکیده انگلیسی

Based on locally linear embedding (LLE) and modified maximizing margin criterion (MMMC), a modified locally linear discriminant embedding (MLLDE) algorithm is proposed for plant leaf recognition in this paper. By MLLDE, the plant leaf images are mapped into a leaf subspace for analysis, which can detect the essential leaf manifold structure. Furthermore, the unwanted variations resulting from changes in period, location, and illumination can be eliminated or reduced. Different from principal component analysis (PCA) and linear discriminant analysis (LDA), which can only deal with flat Euclidean structures of plant leaf space, MLLDE not only inherits the advantages of locally linear embedding (LLE), but makes full use of class information to improve discriminant power by introducing translation and rescaling models. The experimental results on real plant leaf database show that the MLLDE is effective for plant leaf recognition.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issues 14–15, July 2011, Pages 2284–2290
نویسندگان
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