Mulia Octavia, Jesslyn K, Gasim Gasim


Image processing has been commonly used in automatic object identification. These are some methods that can be used for automatic object identification, such as LVQ, K-NN, SVM, and Neural Network. This research specifically bring out the topic about the level accuracy comparison in identification of pear variety using grayscale, HSV, and L*a*b* images in aim to get the best image type for pear image identification using neural network. The feature are gray level co-occurrence matrix feature (energy, entropy, homogeneity, and contrast) from canny edge detection’s image and also color feature. Based on image examination result, grayscale reached its best accuracy for 90% on MSE 1e-10 with 10 hidden layer neurons, HSV reached its best accuracy for 100% on MSE 1e-5 with 20 hidden layer neurons, L*a*b* reached its best accuracy for 100% on MSE 1e-5 with 15 hidden layer neurons. HSV and L*a*b* give the better accuracy for pear variety image identification than grayscale.

Keyword:Image Processing, Pear, Neural Network, Identification, Gray Level Co-occurrence Matrix, Canny, Color.

Full Text:



J. Laseduw, “Kandungan dan Manfaat Buah Pir untuk Kesehatan”,, 6 September 2015.

Agmalaro, MA, Kustiyo, A &AR. Akbar,“Identifikasi Tanaman Buah Tropika Berdasarkan Tekstur Permukaan Daun Menggunakan Jaringan Syaraf Tiruan”, Jurnal Ilmu Komputer Agri - Informatika, vol. 2, no. 2, pp. 73-82, 2013

D. Savakar, “Identification and Classification of Bulk Fruits Images Using Artificial Neural Networks”, International Journal of Engineering and Innovative Technology, vol. 1, no. 3, pp. 36-40, 2012

Danti. A, Madgi, M & Anami, BS, “A Neural Network Based Recognition and Classification of Commonly Used Indian Non Leafy Vegetables”, Modern Education and Computer Science, no. 10, pp. 62-68, 2014

D. Putra, “Pengolahan Citra Digital”, Yogyakarta : Andi Offset, 2010

E. Prasetyo, “Pengolahan Citra Digital dan Aplikasinya Menggunakan Matlab”, Yogyakarta : Andi Offset, 2011.

Rashmi, M. Kumar, R. Saxena, “Algorithm and Technique on Various Edge Detection : A Survey, Signal and Image Processing : An International Journal” , vol. 4, no. 3, pp. 65-75, 2013



  • There are currently no refbacks.

Editorial Office

  • study program in visual communication design
  • Universitas Indo Global Mandiri, Palembang
  • Jl. Jend. Sudirman KM.4 No.629, 20 Ilir D. IV, Kec. Ilir Tim. I, Kota Palembang, Sumatera Selatan 30129.
  • Telpon/Fax: +62711-3227-05
  • Contact :Ahmad Sanmorino (087898273838)

Jurnal Informatika Global

E-ISSN2477-378 P-ISSN: 2302-500X,

MK licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.