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dc.contributor.authorRiyadi, Slamet
dc.contributor.authorAzra, Riza Azyumarridha
dc.contributor.authorSyahputra, Ramadoni
dc.contributor.authorHariadi, Tony K.
dc.date.accessioned2014-12-05T02:40:55Z
dc.date.available2014-12-05T02:40:55Z
dc.date.issued2014-11-25
dc.identifier.citationA. Ito, Y. Aoki, and S. Hashimoto, “Accurate extraction and measurement of fine cracks from concrete block surface image,” in Proceedings of the Annual Conference of the Industrial Electronics Society, vol. 3, pp. 2202–2207, 2002. E. Teomete, V. R. Amin, H. Ceylan, and O. Smadi, “Digital image processing for pavement distress analyses,” in Proceedings of the Mid-Continent Transportation Research Symposium, p. 13, 2005. H. Elbehiery, A. Hefnawy, and M. Elewa, “Surface defects detection for ceramic tiles using image processing and morphological techniques,” in Proceedings of theWorld Academy of Science, Engineering and Technology (PWASET ’05), vol. 5, pp. 158–162, 2005. Liu, S.W; Huang, Jin H; Sung, J.C; Lee, C.C, “Detection of cracks using neural networks and computational mechanics”, Computer Methods in Applied Mechanics and Engineering, ISSN 0045-7825, 2002, Volume 191, Issue 25, pp. 2831 – 2845 M. Coster and J.-L. Chermant, “Image analysis and mathematical morphology for civil engineering materials,” Cement and Concrete Composites, vol. 23, no. 2, pp. 133–151, 2001. S. Iyer and S. K. Sinha, “A robust approach for automatic detection and segmentation of cracks in underground pipeline images,” Image and Vision Computing, vol. 23, no. 10, pp. 921– 933, 2005. Saar, T; Saar, T; Talvik, O; Talvik, O, “Automatic Asphalt pavement crack detection and classification using Neural Networks”, 12th Biennial Baltic Electronics Conference 2010, pp. 345 – 348 Sylvie Chambon and Jean-Marc Moliard. 2011. Automatic road pavement assessment with image processing: review and comparison. International Journal of Geophysics Vol. 2011. T. S. Nguyen, M. Avila, S. Begot, F. Duculty, and J.-C. Bardet, “Automatic detection and classification of defect on road pavement using anisotropy measure,” in Proceedings of the European Signal Processing Conference, pp. 617–621, 2009. Umesha, P.K; Ravichandran, R; Sivasubramanian, K, 2009, “Crack Detection and Quantification in Beams Using Wavelets”, Computer-Aided Civil and Infrastructure Engineering, Volume 24, Issue 8, p. 593 Zalama, Eduardo; Gómez‐García‐Bermejo, Jaime; Medina, Roberto; Llamas, José, 2013, “Road Crack Detection Using Visual Features Extracted by Gabor Filter”, Computer‐Aided Civil and Infrastructure Engineering, ISSN 1093-9687, 05/2014, Volume 29, Issue 5, pp. 342 – 358en_US
dc.identifier.issn2339-028X
dc.identifier.urihttp://hdl.handle.net/11617/5062
dc.description.abstractKondisi permukaan jalan raya perlu diperiksa secara secara rutin untuk mendeteksi keberadaan retak permukaan yang bisa mengakibatkan ketidaknyamanan berkendaraan dan mengancam keselamatan.Sekarang ini, pemeriksaan dilaksanakan secara manual dimana petugas menyusuri sepanjang jalan dan kemudian mencatat serta menandai keberadaan retak.Cara konvensional ini memerlukan waktu lama, tenaga kerja yang banyak dan kurang tepat karena faktor manusia.Untuk mengatasinya, penelitian ini mengusulkan penggunaan teknik pengolahan citra digital untuk mendeteksi keberadaan retak permukaan jalan.Tahapan penelitian dimulai dengan pengumpulan data permukaan jalan, pengembangan metode pengolahan citra dan pengujian pada citra.Metode pengolahan citra yang dikembangkan menggunakan kombinasi teknik tresholding, median filter dan morphological closing.Metode telah diterapkan pada citra permukaan jalan dan diperoleh akurasi deteksi retak sebesar 85% dan kecepatan proses 4,25 detik per citra. Kesimpulannya, teknik yang dikembangkan berhasil mendeteksi keberadaan retak dengan akurat dan cepat.en_US
dc.publisherUniversitas Muhammadiyah Surakartaen_US
dc.subjectpengolahan citraen_US
dc.subjectretak permukaan jalanen_US
dc.subjecttresholdingen_US
dc.subjectmedian filteren_US
dc.subjectmorphological closingen_US
dc.titleDeteksi Retak Permukaan Jalan Raya Berbasis Pengolahan Citra dengan Menggunakan Kombinasi Teknik Thresholding, Median Filter dan Morphological Closingen_US
dc.typeArticleen_US


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