Optical Character Recognition Citra Kata Kanji Menggunakan Ekstraksi Fitur Algoritma Chain Code dan Algoritma L1-Metric
DOI:
https://doi.org/10.22441/format.2020.v9.i2.002Keywords:
Chain Code, Ekstraksi Fitur, Kanji, L1 Metric, Manhattan Distance, OCRAbstract
Kanji merupakan salah satu bahasa yang berasal dari negara Jepang. Bahasa Jepang sendiri telah menyebar di berbagai negara terutama di Indonesia. Namum dikarenakan bahasa Jepang bukanlah bahasa yang mudah dipelajari karena bahasa Jepang tidak termasuk kedalam bahasa Internasional. Oleh karena itu diperlukan sistem yang bisa membaca bahasa aksara bahasa Jepang khususnya kanji. Penelitian ini akan difokuskan pada perancangan aplikasi pengenalan karakter optik dari aksara kanji menggunakan ekstraksi fitur chain code untuk melakukan pengenalan pola dari citra aksara kanji dan perhitungan jarak manhattan distance (L1 Metric). Dalam membangun aplikasi digunakan bahasa pemrograman pascal menggunakan Lazarus IDE dan integrasi sistem basis data. Proses dalam penelitian ini terdiri dari 5 tahap yaitu pre-processing, segmentasi, filtering spasial linier, ekstraksi fitur chain code, dan perhitungan jarak nilai fitur. Jarak citra kanji yang diuji akan dibandingkan dengan citra kanji yang sudah dilatih di basis data untuk mencari jarak terkecil. Hasil pengujian yang dilakukan dengan algoritma chain code dan manhattan distance (L1 Metric) menunjukkan bahwa sebesar 21.82% citra tulisan tangan kanji berhasil dikenali dan 78.18% mengalami kegagalan dalam mengenali citra yang diujiDownloads
References
N. Venkata Rao, A. S. C. S. Sastry, A. S. N. Chakravarthy, and P. Kalyanchakravarthi, “Optical character recognition technique algorithms. ISSN : 1992-8645,” J. Theor. Appl. Inf. Technol., vol. 83, no. 2, pp. 275–282, 2016.
D. Putra, Pengolahan Citra Digital. ISBN : 978-979-29-1443-6. Yogyakarta: ANDI, 2010.
T. M. S. Mulyana, “Efek High Pass Filtering Dengan Koefesien Nol Pada Citra Biner. ISSN : 2579-6402,” J. Muara Sains, Teknol. Kedokt. dan Ilmu Kesehat., vol. 1, no. 1, pp. 75–83, 2017, doi: 10.24912/jmstkik.v1i1.394.
P. Liu, J. Zhang, and K. Guo, “A Parking-Lines Recognition Algorithm Based on Freeman Chain Code. ISBN : 978-1-4799-8645-3,” 2015 7th Int. Conf. Intell. Human-Machine Syst. Cybern., vol. 2, pp. 349–352, 2015, doi: 10.1109/IHMSC.2015.247.
Theresia and C. Simon, “Pengenalan Karakter Menggunakan Algoritma Berbasis Chain Node. ISSN : 2477-5894,” Proceeding 2nd Informatics Conf. 2016 June 18, 2016, Univ. Budi Luhur, Jakarta, Indones., vol. 2016, pp. 65–91, 2016.
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