Authors:

Ni Luh Wiwik Sri Rahayu Ginantra

Abstract:

“Batik motifs are the base or the blueprint of batik patterns which serve as the core of the batik image design, and therefore the meaning of a sign, symbol or logo in a batik work can be revealed through its motifs. Visual identification requires visual skills and knowledge in classifying patterns formed in a batik image. Lack of media providing information on batik motifs makes the public unable to have sufficient information about batik motifs. Looking at this phenomenon, this study is conducted in order to perform visual identification using a computer that can assist and facilitate in identifying the types of batik. The methods used for batik image recognition are the Co-occurrence Matrix method to provide extraction of batik texture features, and the Geometric Moment Invariant method, while K Nearest Neighbor is used to classify batik images. The results on the accuracy values obtained reveal that the of 80%, compared to the accuracy value result using the Co-occurrence Matrix method that is 70%.”

Keywords

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References

  • [1] W. Eka Widya, “Klasifikasi Motif Batik Menggunakan Metode Transformasi Paket Wavelet,” 2013.
  • [2] D. Putra, Pengolahan Citra Digital. Yogyakarta: Andi, 2010.
  • [3] T. Sergios, Pattern Recognition Second Edition. USA: Academic Press An Imprint Of Elsevier, 2003.
  • [4] A. Winarni, I. K. G. D. Putra, N. Ary, and E. Dewi, “Ekstraksi Ciri Warna dan Tekstur Untuk Temu Kembali Citra Batik,” 2012.

PDF:

https://jurnal.harianregional.com/lontar/full-19704

Published

2016-03-30

How To Cite

GINANTRA, Ni Luh Wiwik Sri Rahayu. Deteksi Batik Parang Menggunakan Fitur Co-Occurence Matrix Dan Geometric Moment Invariant Dengan Klasifikasi KNN.Lontar Komputer : Jurnal Ilmiah Teknologi Informasi, [S.l.], p. 40-50, mar. 2016. ISSN 2541-5832. Available at: https://jurnal.harianregional.com/lontar/id-19704. Date accessed: 02 Jun. 2025. doi:https://doi.org/10.24843/LKJITI.2016.v07.i01.p05.

Citation Format

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Issue

Vol. 7, No. 1 April 2016

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License