title: Computer vision-based method for classification of wheat grains using artificial neural network.
abstract: BACKGROUND
  A simplified computer vision-based application using artificial neural network (ANN) depending on multilayer perceptron (MLP) for accurately classifying wheat grains into bread or durum is presented. The images of 100 bread and 100 durum wheat grains are taken via a high-resolution camera and subjected to pre-processing. The main visual features of four dimensions, three colors and five textures are acquired using image-processing techniques (IPTs). A total of 21 visual features are reproduced from the 12 main features to diversify the input population for training and testing the ANN model. The data sets of visual features are considered as input parameters of the ANN model. The ANN with four different input data subsets is modelled to classify the wheat grains into bread or durum. The ANN model is trained with 180 grains and its accuracy tested with 20 grains from a total of 200 wheat grains.
  
  
  RESULTS
  Seven input parameters that are most effective on the classifying results are determined using the correlation-based CfsSubsetEval algorithm to simplify the ANN model. The results of the ANN model are compared in terms of accuracy rate. The best result is achieved with a mean absolute error (MAE) of 9.8 × 10-6by the simplified ANN model.
  
  
  CONCLUSIONS
  This shows that the proposed classifier based on computer vision can be successfully exploited to automatically classify a variety of grains. © 2016 Society of Chemical Industry.
authors.affiliation: Department of Electrical and Electronics Engineering, Engineering Faculty, Karamanoglu Mehmetbey University, 70100, Karaman, Turkey.
authors.forename: Kadir
authors.initials: K
authors.lastname: Sabanci
authors.affiliation: Department of Electrical and Electronics Engineering, Engineering Faculty, Karamanoglu Mehmetbey University, 70100, Karaman, Turkey.
authors.forename: Ahmet
authors.initials: A
authors.lastname: Kayabasi
authors.affiliation: Department of Electrical and Electronics Engineering, Engineering Faculty, Karamanoglu Mehmetbey University, 70100, Karaman, Turkey.
authors.forename: Abdurrahim
authors.initials: A
authors.lastname: Toktas
mesh_terms: D000465:Algorithms; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016571:Neural Networks, Computer; D012639:Seeds / Q000737:chemistry / Q000145:classification*; D014908:Triticum / Q000737:chemistry* / Q000145:classification
keywords: artificial neural network (ANN); classification; image processing; multilayer perceptron; wheat grains