Application of multispectral image texture to discriminating tea categories based on DCT and LS-SVM

Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis

Volumn 29, Issue 5, 2009, Pages 1382-1385

  Wu, Di ^a   Chen, Xiao Jing ^a,b   He, Yong ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b XIAMEN UNIVERSITY   (China)

Author keywords

Discrete cosine transform; Least squares support vector machine; Multi spectral image; Tea; Texture feature

Indexed keywords

CLASSIFICATION RATES; DIGITAL IMAGES; FILTERED IMAGES; LEAST SQUARES-SUPPORT VECTOR MACHINE; MULTI-SPECTRAL; MULTI-SPECTRAL IMAGE; NEAR-INFRARED WAVEBAND; NIR IMAGES; NON-DESTRUCTIVE METHODS; ON-LINE APPLICATIONS; TEA; TEXTURE FEATURE; TEXTURE RECOGNITION; VISIBLE SPECTRUMS; WAVE BANDS; WHOLE PROCESS;

COSINE TRANSFORMS; CURVE FITTING; IMAGE CODING; IMAGE RETRIEVAL; INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; RESEARCH AIRCRAFT; SUPPORT VECTOR MACHINES; TEXTURES;

DISCRETE COSINE TRANSFORMS;

ARTICLE; ARTIFICIAL INTELLIGENCE; BEVERAGE; CLASSIFICATION; COLOR; INFRARED SPECTROPHOTOMETRY; QUALITY CONTROL; REGRESSION ANALYSIS; STATISTICS;

ARTIFICIAL INTELLIGENCE; BEVERAGES; COLOR; LEAST-SQUARES ANALYSIS; QUALITY CONTROL; SPECTROPHOTOMETRY, INFRARED;

EID: 65549144015     PISSN: 10000593     EISSN: None     Source Type: Journal    
DOI: 10.3964/j.issn.1000-0593(2009)05-1382-04     Document Type: Article

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