کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
525910 869039 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Orthogonal locally discriminant spline embedding for plant leaf recognition
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Orthogonal locally discriminant spline embedding for plant leaf recognition
چکیده انگلیسی


• OLDSE explicitly considers the intrinsic leaf manifold structure.
• OLDSE takes local structure and discriminant information into consideration simultaneously.
• OLDSE seeks to find a set of orthogonal basis functions.

Based on local spline embedding (LSE) and maximum margin criterion (MMC), two orthogonal locally discriminant spline embedding techniques (OLDSE-I and OLDSE-II) are proposed for plant leaf recognition in this paper. By OLDSE-I or OLDSE-II, the plant leaf images are mapped into a leaf subspace for analysis, which can detect the essential leaf manifold structure. Different from principal component analysis (PCA) and linear discriminant analysis (LDA) which can only deal with flat Euclidean structures of plant leaf space, OLDSE-I and OLDSE-II not only inherit the advantages of local spline embedding (LSE), but makes full use of class information to improve discriminant power by introducing translation and rescaling models. The proposed OLDSE-I and OLDSE-II methods are applied to recognize the plant leaf and are examined using the ICL-PlantLeaf and Swedish plant leaf image databases. The numerical results show compared with MMC, LDA, SLPP, and LDSE, the proposed OLDSE-I and OLDSE-II methods can achieve higher recognition rate.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 119, February 2014, Pages 116–126
نویسندگان
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