PENGGUNAAN MOMEN INVARIANT, ECCENTRICITY, DAN COMPACTNESS UNTUK KLASIFIKASI MOTIF BATIK DENGAN K-NEAREST NEIGHBOUR
Abstract: Batik classification
which have diverse motifs need to be done to distinguish a pattern with
another. In this paper, we present batik motifs(Ceplok, Parang, Semen, and
Nitik) classification using Hu Moment Invariants, Eccentricity, and Compactness
feature description. In classification stage, K-nearest neighbor have been
used, which is traditional nonparametric statistical classifier. Set of
different experiments on binary images regular, opening image, and closing
image of 200 images Batik from some batik literature published by Dinas
Perindustrian, Perdagangan, dan Koperasi DIY have been done and variety of
results have been presented. The results showed that the best classification
result obtained from Hu Moment Invariants feature description.
Penulis: Nugroho Agus Haryono,
Widi Hapsari, Angelique Angesti, Stheffany Felixiana
Kode Jurnal: jptinformatikadd150374
