IMPLEMENTASI METODE MARR-HILDERTH OPERATOR UNTUK MENDETEKSI TEPI CITRA IKONOS

 (*)Yusman Zalukhu Mail (Program Studi Teknik Informatika, STMIK Budi Darma, Medan, —)
 Hery Sunandar (Program Studi Teknik Informatika, STMIK Budi Darma, Medan, —)
 Rivalri Kristianto Hondro (Program Studi Teknik Informatika, STMIK Budi Darma, Medan, —)

(*) Corresponding Author

Abstract

Ikonos imagery is a satellite image that has high spatial resolution with an accuracy of one meter pixels for panchromatic and four meters to multispektral. Ikonos imagery is often used to map the process, view, measure and memoniotring areas of work/activities on the Earth. Ikonos image of Government also often use it for things like national security evaluation against the occurrence of the disaster, city planning, mineral exploration and mine planning monitoring of agriculture, and others. Image digital imaging results over long distances using satellite is often there are disturbances in the form of light distortion, noise or other distractions that cause the object on the image less obvious or obscure. This discussion on the research being done is knowing the process of detection on image by calculating the difference between two dots are bertetanggan, and is in the process of smoothing and thresholding on image ikonos. The methods used in this research is a method of Marr-Hilderth. In addition, a process that is done on this research is conducting a testing method against Marr-Hilderth, which can be implemented to fix the blurry objects on images ikonos. The results of this research is to generate image ikonos with display clear object with the menerapakan method of the Marr-Hilderth and tested using the matlab application version 7.8 (r2009a).

Keywords: Ikonos image, image processing, method of Marr-Hilderth, Matlab 7.8

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References

K. J. Pithadiya, C. K. Modi, and J. D. Chauhan, “Comparison of optimal edge detection algorithms for liquid level inspection in bottles,” in 2009 2nd International Conference on Emerging Trends in Engineering and Technology, ICETET 2009, 2009, pp. 447–452.

A. Sulistyohati, T. Hidayat, K. Kunci: Ginjal, S. Pakar, and M. Dempster-Shafer, “Aplikasi Sistem Pakar Diagnosa Penyakit Ginjal Dengan Metode Dempster-Shafer,” Semin. Nas. Apl. Teknol. Inf., vol. 2008, no. Snati, pp. 1907–5022, 2008.

D. W. Widodo, . K., and E. Boedijanto, “Perancangan Sistem Pakar Deteksi Dini Tumbuh Kembang Anak Berbasis Multimedia,” Sisfotenika, vol. 4, no. 2, pp. 128–139, 2014.

B. Y. Dwiandiyanta, U. Atma, and J. Yogyakarta, “Pengembangan Aplikasi Deteksi Tepi Citra Medis menggunakan Operator Kompas Disusun oleh : Program Studi Teknik Informatika Fakultas Teknologi Industri,” 2011.

Y. G.H.L and Y. Melita, “Segmentasi Iris Mata Dengan Menggunakan Transformasi Hough,” J. Ilm. Teknol. Inf. Asia, vol. 7, no. 2, 2013.

Sinaga ASRM, “Implemetentasi Teknik Thresholding Pada Segmentasi Citra Digital,” Mantik Penusa, vol. 1, pp. 48–51, 2017.

T. Zebua, R. K. Hondro, and E. Ndruru, “Message Security on Chat App based on Massey Omura Algorithm,” Int. J. Inf. Syst. Technol., vol. 1, no. 2, pp. 16–23, 2018.

R. E. Wibowo, R. R. Isnanto, and A. A. Zahra, “Perbandingan Kinerja Operator Sobel dan Laplacian of Gaussian ( LoG ) Terhadap Acuan Canny untuk Mendeteksi Tepi Citra,” Transient, vol. 3, no. 1, pp. 1–6, 2014.

I. D. Reja and A. J. Santoso, “Pengenalan Motif Sarung ( Utan Maumere ) Menggunakan Deteksi Tepi,” Semin. Nas. Teknol. Inf. Komun. Terap., vol. 2013, no. November, pp. 161–168, 2013.

N. Effendy, R. Imanto, J. T. Fisika, F. Teknik, U. Gadjah, and J. S. Tiruan, “Deteksi Pornografi Pada Citra Digital Menggunakan Pengolahan Citra dan Jaringan Syaraf Tiruan,” Proc. Natl. Conf. Inf. Technol. Res., 2008.

D. Kurnianto, I. Soesanti, and H. A. Nugroho, “Deteksi Iris Berdasarkan Metode Black Hole dan Circle Curve Fitting,” J. Infotel, vol. 5, no. 2, pp. 10–16, 2013.

R. I. SAA Bowo, A Hidayatno, “Analisis deteksi tepi untuk mengidentifikasi pola daun,” Undergrad. thesis, Diponegoro Univ., pp. 1–7, 2011.

and N. K. A. W. Krisna Putra, Putu Teguh, “Pengolahan Citra Digital Deteksi Tepi Untuk Membandingkan Metode Sobel, Robert dan Canny,” MERPATI, vol. 2, no. 2, pp. 253–261, 2014.

V. A. Dave and P. S. K. Hadia, “Liquid Level and Cap Closure United Inspection using Image Processing,” Int. J. Innov. Res. Sci. Technol., vol. 1, no. 12, pp. 62–68, 2015.

M. Moganti and F. Ercal, “A Subpattern Level Inspection System for Printed Circuit Boards,” Comput. Vis. Image Underst., vol. 70, no. 1, pp. 51–62, 1998.

M. Yazdani, W. Fraczak, F. Welfeld, and I. Lambadaris, “Two level state machine architecture for content inspection engines,” in Proceedings - IEEE INFOCOM, 2006.

A. Majumder, “Image processing algorithms for improved character recognition and components inspection,” in 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings, 2009, pp. 531–536.

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