Automated identification and visualization of food defects using RGB imaging: Application to the detection of red skin defect of raw hams

Innovative Food Science and Emerging Technologies

Volumn 16, Issue , 2012, Pages 417-426

  Ulrici, Alessandro ^a   Foca, Giorgia ^a   Ielo, Maria Cristina ^a   Volpelli, Luisa Antonella ^a   Lo Fiego, Domenico Pietro ^a  

^a UNIVERSITY OF MODENA AND REGGIO EMILIA   (Italy)

Author keywords

Defect detection; Feature selection; Multivariate classification; Raw ham red skin defect; RGB images; Wavelet transform

Indexed keywords

AUTOMATED IDENTIFICATION; CLASSIFICATION EFFICIENCY; CLASSIFICATION MODELS; COMPREHENSIVE METHOD; DEFECT DETECTION; HISTORICAL DATA; HUMAN EVALUATION; IMAGE FEATURES; INFORMATION CONTENTS; MULTI VARIATE ANALYSIS; MULTIVARIATE CLASSIFICATION; NON-TRANSFERABILITY; PARTIAL LEAST SQUARES-DISCRIMINANT ANALYSIS; PRE-SELECTION; RED GREEN BLUES; RGB IMAGES; RGB IMAGING; SEGMENTED IMAGES; SELECTION TECHNIQUES; SKIN DEFECTS; SPECIFIC PROBLEMS; SUBJECTIVE METHODS; TEST SETS; WAVELET PACKET;

ALGORITHMS; DEFECTS; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; WAVELET TRANSFORMS;

IMAGE RECONSTRUCTION;

SUIDAE;

EID: 84870563451     PISSN: 14668564     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ifset.2012.09.008     Document Type: Article

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