Guang pu xue yu guang pu fen xi, 2010-10, Vol.30 (10), p.2739
2010
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Details
- Autor(en) / Beteiligte
- Titel
- LLE-SVM classification of apple mealiness based on hyperspectral scattering image
- Ist Teil von
- Guang pu xue yu guang pu fen xi, 2010-10, Vol.30 (10), p.2739
- Ort / Verlag
- China
- Erscheinungsjahr
- 2010
- Quelle
- MEDLINE
- Beschreibungen/Notizen
- Apple mealiness degree is an important factor for its internal quality. hyperspectral scattering, as a promising technique, was investigated for noninvasive measurement of apple mealiness. In the present paper, a locally linear embedding (LLE) coupled with support vector machine (SVM) was proposed to achieve classification because of large number of image data. LLE is a nonlinear lowering dimension method, which reveals the structure of the global nonlinearity by the local linear joint. This method can effectively calculate high-dimensional input data embedded in a low-dimensional space manifold. The dimension reduction of hyperspectral data was classified by SVM. Comparing the LLE-SVM classification method with the traditional SVM classification, the results indicated that the training accuracy obtained with the LLE-SVM was higher than that just with SVM; and the testing accuracy of the classifier changed a little before and after dimensionality reduction, and the range of fluctuation was less than 5%. It is
- Sprache
- Chinesisch
- Identifikatoren
- ISSN: 1000-0593DOI: 10.3964/j.issn.1000-0593(2010)10-2739-05Titel-ID: cdi_pubmed_primary_21137411
- Format
- –
- Schlagworte
- Food Analysis - methods, Malus, Spectrum Analysis, Support Vector Machine