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Widi Hapsari
Program Studi Teknik Informatika, Universitas Kristen Duta Wacana
Computer Science & IT

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PENGGUNAAN MOMEN INVARIANT, ECCENTRICITY, DAN COMPACTNESS UNTUK KLASIFIKASI MOTIF BATIK DENGAN K-NEAREST NEIGHBOUR Nugroho Agus Haryono; Widi Hapsari; Angelique Angesti; Stheffany Felixiana
Jurnal Informatika Vol 11, No 2 (2015): Jurnal Teknologi Komputer dan Informatika
Publisher : Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.395 KB) | DOI: 10.21460/inf.2015.112.411

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.
Co-Authors Angelique Angesti Nugroho Agus Haryono Stheffany Felixiana