Identification of some spanish olive cultivars using image processing techniques

BEYAZ A., ÖZKAYA M. T., İÇEN D.

SCIENTIA HORTICULTURAE, cilt.225, ss.286-292, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 225
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1016/j.scienta.2017.06.041
  • Dergi Adı: SCIENTIA HORTICULTURAE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.286-292
  • Anahtar Kelimeler: Artificial vision, Image analysis, Olive fruit, Olive stone, Varietal identification, COMPUTER VISION, CLASSIFICATION, CHEMOMETRICS
  • Ankara Üniversitesi Adresli: Evet

Özet

The aim of this research was to identify some Spanish olive cultivars using image processing techniques. For this purpose, Lechin De Granada, Arbequina, Picual, Verdial De V-M, Picudo, Hojiblanca and Empeltre Olive cultivars were identified utilizing the image processing and analysis techniques. Therefore, images of olives taken as 300 dpi with the 2896 x 1944 pixels, were captured using a DSLR camera, and evaluations of pixels were used for considering the pixel distribution and dimension measurements. LabVIEW Vision Assistant v2013 (NI) and Image j (NIH) software were used for image analysis procedures. Artificial Neural Network analysis were used to assess information of the length, width and color data results obtained from the fruits and stones (olive stones). All cultivars were identified. In addition, different classification techniques were applied to the olive stone and fruit data with the help of SPSS v22. Clementine v12 was used as a data mining software package from SPSS. The cultivars were identified 90% from dimensions with Artificial Neural Networks.