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All Journal Majalah Ilmiah Teknologi Elektro Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Jurnal Bangkit Indonesia Majalah Ilmiah Teknologi Elektro
I Putu Gd Sukenada Andisana
STMIK Bandung Bali
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Public Health

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Journal : Majalah Ilmiah Teknologi Elektro

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Pengenalan Dan Klasifikasi Citra Tekstil Tradisional Berbasis Web Menggunakan Deteksi Tepi Canny, Local Color Histogram Dan Co-Occurrence Matrix I Putu Gd Sukenada Andisana; Made Sudarma; I Made Oka Widyantara
Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1149.427 KB) | DOI: 10.24843/MITE.2018.v17i03.P15

Abstract

the use of traditional Indonesian textile motifs is influenced by elements of nature, environment and culture that develop in the community. Materials, motifs and techniques for making traditional textiles are different from one region to another. The use of information technology in preservation and providing knowledge to the public can made in the form of software that can match the pattern of images or photos while performing traditional textile classifications. The input in this study is an image of a patterned texture. The software through the pattern recognition process will perform calculations and produce values ??that can be matched in the sample database that has previously been processed. The method used is the color feature extraction with the Local Color Histogram method, texture feature extraction with the Co-occurrence matrix method, and the extraction of shape features with the Canny Edge Detection method. Each feature extraction will produce a vector. The data used consisted of 10 textile groups namely endek bali, songket bali, tenun dayak, tenun ikat, sasirangan, kain besurek, ulos, sutera bugis, kain gringsing. Classification method by using K-Nearest Neighborhood (K-NN). The results of this study are the highest accuracy values ??for extraction of texture features and the lowest accuracy values ??for the combination of extraction of shape and color features.
Co-Authors A. -, Winarni, A. Dadan Abdullah I Gede Arya Purusa Dhana I Gede Made Karma I Gusti Ngurah Ary Widiatmika I Made Oka Widyantara I Nyoman Trisna Wijaya Giri I.K -, Mardika, I.K Ibnu Atho'illah M.R. -, Romdoni, M.R. Made Sudarma Mardika, I.K - N.Y.E -, Smrti, N.Y.E Ni Nyoman Emang Smrti Nuni Diyah Ansori Romdoni, M.R. - Smrti, N.Y.E - Winarni, A. -