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Image Segmentation and Bruise Identification on Potatoes Using a Kohonen's Self‐Organizing Map
Author(s) -
Marique Thierry,
Pennincx Stephanie,
Kharoubi Ammar
Publication year - 2005
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/j.1365-2621.2005.tb11469.x
Subject(s) - self organizing map , bruise , artificial intelligence , segmentation , pattern recognition (psychology) , spots , identification (biology) , computer science , colored , computer vision , botany , biology , medicine , cluster analysis , materials science , surgery , composite material
Potato quality includes a low incidence of colored bruises resulting from bad storage or manipulation practices. We developed a procedure to process and segment potato images by using Kohonen's self‐organizing map. Anomalous regions could be distinguished on 3 potato varieties. Bruises that were very dissimilar in appearance were correctly identified, and some particular defects such as green spots could be located as well.