Title of article :
Olive classification according to external damage using image analysis Original Research Article
Author/Authors :
M.T. Riquelme، نويسنده , , P. Barreiro، نويسنده , , M. Ruiz-Altisent، نويسنده , , C. Valero، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
9
From page :
371
To page :
379
Abstract :
The external appearance of an olive’s skin is the most decisive factor in determining its quality as a fruit. This work tries to establish a hierarchical model based on the features extracted from images of olives reflecting their external defects. Seven commercial categories of olives, established by product experts, were used: undamaged olives, mussel-scale or ‘serpeta’, hail-damaged or ‘granizo’, mill or ‘rehús’, wrinkled olive or ‘agostado’, purple olive and undefined-damage or ‘molestado’. The original images were processed using segmentation, colour parameters and morphological features of the defects and the whole fruits. The application of three consecutive discriminant analyses resulted in the correct classification of 97% and 75% of olives during calibration and validation, respectively. However the correct classification percentages vary greatly depending on the categories, ranging 80–100% during calibration and 38–100% during validation.
Keywords :
External damages , Artificial vision , Sorting fruit , Table olives , Image processing
Journal title :
Journal of Food Engineering
Serial Year :
2008
Journal title :
Journal of Food Engineering
Record number :
1167864
Link To Document :
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