3D reconstruction and feature extraction for agricultural produce grading

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Panitnat Yimyam and Adrian F. Clark",
  booktitle =    "2016 8th International Conference on Knowledge and
                 Smart Technology (KST)",
  title =        "{3D} reconstruction and feature extraction for
                 agricultural produce grading",
  year =         "2016",
  pages =        "136--141",
  abstract =     "This paper examines the grading of agricultural
                 produce from multiple images using colour and texture
                 properties. Some types of agricultural produce need to
                 be inspected from multiple views in order to assess the
                 entire appearance; however, using multiple images may
                 obtain redundant data. Therefore, techniques are
                 presented to reconstruct a 3D object, create new images
                 without duplicated object areas and extract colour and
                 texture features for evaluation. The performance of
                 using multiple view images without duplicated object
                 regions is compared with those of using only top-view
                 images and the original multiple view images.
                 Experiments are performed on apple and guava grading
                 using kNN, NN, SVM and GP for classification.
                 Performance differences from the different image sets
                 are compared using McNemar's test and the Friedman
                 test. It is found that the performance when using
                 multiple view images is superior to that when using
                 single-view images for all experiments. Employing
                 features extracted from multiple view images without
                 object area duplication achieves significantly higher
                 accuracy than employing the original multiple view
                 images for apple grading, but their performances do not
                 differ significantly for guava inspection.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/KST.2016.7440482",
  month =        feb,
  notes =        "Science and Social Sciences, Burapha University Sakaeo
                 Campus, Sakaeo, Thailand

                 Also known as \cite{7440482}",

Genetic Programming entries for Panitnat Yimyam Adrian F Clark