Implementation of Fuzzy C-Means Algorithm with Lossy Method for Sasirangan Image Compression
DOI:
https://doi.org/10.59535/jece.v2i1.222Keywords:
Compress, Fuzzy C-Means, Sasirangan, Vector quantizationAbstract
Sasirangan as the Banjar people's creative work is a typical icon of South Kalimantan and Widely known for its patterns and uniqueness which highly demanded by local, national and foreign people. Sasirangan textile marketing using the marketplace, Sasirangan image with patterns of different colours have large storage capacity, as well as uploading images of Sasirangan patterns in e-commerce requires large bandwidth, while the constraints on MSME entrepreneurs have limited Internet bandwidth access. Image compression aims to convert data files into smaller files for efficient storage and effective data transmission. The vector quantization method is a mapping of image data in the form of irregular bits, so the mapping uses the fuzzy C-mean algorithm. The achieved compression kulat kurikit.jpg is higher than that of other images, with a compression ratio of 88.5233600% and a file size of 566 KB. a better quality than the others due to its more uniform grey scale colour composition for the same block vector and codebook.
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Menteri Pendidikan dan Kebudayaan Republik Indonesia. (2013). Keputusan Menteri Pendidikan dan Kebudayaan Republik Indonesia Nomor 238/M/2013 tentang Warisan Budaya Takbenda Indonesia Tahun 2013.
Harapan Kita Yayasan. (1995). Kain-kain Non Tenun Indonesia, ISBN 979-8735-03-X, Perum Percetakan Negara Republik Indonesia.
A. Pratomo, E. Najwaini, A. Irawan and M. Risa. (2018). Optimasi E-Commerce dengan Penerapan Teknik SEO (Search Engine Optization) untuk Meningkatkan Penjualan Pada UKM Nida Sasirangan, vol. Vol 1 No 01, pp. 35-47, Jurnal Impact: Implementation and Action.
Z. Almas. (2018). Nilai-Nilai dalam Motif Kain Sasirangan, Vol 07 No 2, pp. 210-220, jurnal Socius.
Muchid. (2015). Pemberdayaan Usaha Mikro, Kecil, Dan Menengah (UMKM) Sebagai Salah Satu Upaya Penanggulangan Kemiskinan. Jurnal Ekonomi Dan Pendidikan, 2(1).
Safaruddin Hidayat Al Ikhsan, Fety Fatimah, Riyan Saputra Irawan. (2019). “Aplikasi Android Sebaran Lokasi UMKM di Kota Bogor Dengan Formula Haversine.” KREA-TIF, Jurnal Teknik Informatika 7 : 15
Veronica Lusiana, Budi Hartono. (2017) “Praproses Citra Menggunakan Kompresi Citra, Perbaikan Kontras, Dan Kuantisasi Piksel.” Prosiding SINTAK 2017: 5.
Gonzales R. C. and Woods R. E (2002) Digital Image Processing Third Edition. Pearson Education International
Vasuki A and Vanathi P. T (2006) A review of vector quantization techniques. IEEE Journal and magazine.
Boopathy G and Arockiasamy S (2010) Implementation of Vector Quantization for Image Compression - A Survey. Global Journal of Computer Science and Technology. Vol. 10 Issue 3 (Ver 1.0).
Wang, et al. (2002) A Universal Image Quality Index”, IEEE Proc, Vol.9, No.3, pp.81-84.
Widiyono. (2022). “Metode Fuzzy Vector Quantization Untuk Kompresi Citra RGB Motif Batik Pekalongan”, Smart Comp Vol. 11 No. 1 Januari.
Ida Afriliana, Arfan Haqiqi Sulasmoro, Ali Sofyan. (2019). “Implementasi Fuzzy Sugeno Untuk Kinerja Pengajaran Dosen.” Smart Comp ,: 4
R. Miftahur, A. Ida. (2013). “Teknik Kompresi Citra Menggunakan Metode Vektor Kuantisasi Berbasis Fuzzy C-Means.” eprints.upnjatim.ac.id : 8
Yuniarti, Anny, Nadya Anisa Syafa, Handayani Tjandrasa. (2010). Aplikasi Kompresi Citra Berbasis Rough Fuzzy Set.
Delport V and Liesch D (1994) Fuzzy-c-mean algorithm for Codebook Design in Vector Quantisation. Electronics Letters. Vol. 30. No.13. IEEE
Bezdek J. C, Ehrlich R, and Full W (1984) FCM: The Fuzzy C-Means Clustering Algorithm. Computer and Geosciences vol. 10. no. 2-3. pp.191-203.
Gersho, A.; Gray, R.M. Vector Quantization and Signal Compression; Kluwer Academic Publishers: Boston, MA, USA, 1992
Horng, M.-H.; Jiang, T.-W. Image Vector Quantization Algorithm via Honey Bee Mating Optimization. Inf. Sci. 2012, 38, 1382–1392.
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