Ekstraksi Fitur Warna dengan Histogram HSV untuk Klasifikasi Motif Songket Palembang

  • Yohannes Yohannes Universitas Multi Data Palembang
  • Muhammad Ezar Al Rivan Universitas Multi Data Palembang
  • Siska Devella Universitas Multi Data Palembang
  • Meiriyama Meiriyama Universitas Multi Data Palembang
Keywords: Classification, Histogram, HSV, Songket, SVM

Abstract

Palembang Songket is a type of traditional woven cloth that has been registered as Indonesia's intangible cultural heritage since 2013. Palembang Songket has many motifs including Bunga Cina, Cantik Manis, and Pulir. The motifs on Palembang Songket have different meanings which can influence the selling price of the Songket. Recognition and classification of Palembang Songket types and motifs can be done by utilizing computer technology such as digital image processing and machine learning. In this research, the classification of Palembang Songket motifs was carried out using color features with histograms in Hue, Saturation, and Value (HSV) space and the Support Vector Machine (SVM) machine learning algorithm. Testing was carried out on a classification system using 45 test images. The histogram of HSV and SVM methods with the best kernel, namely RBF, were able to classify Palembang Songket motifs with an accuracy of 0.956; precision of 0.94; recall of 0.933; and f1-score of 0.931.

References

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Published
2024-06-10

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