Purwarupa Sistem Prediksi Luas dan Hasil Panen Padi suatu Wilayah menggunakan Pengolahan Citra Digital dengan Metode Sobel dan Otsu
Ardya Yunita Putri(1*), Raden Sumiharto(2)
(1) 
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
Area and paddy crop yield prediction system of an area using image processing by Sobel Otsu’s method is one of system that utilize aerial photo data for measuring area and prediction of its crop yield. Otsu’s method is used to thresholding process and Sobel’s method is used to detect paddy field’s edges that will calculate its area. Then filtering process so that the scanning process white pixels are counted only exist in the desired region. After the amount of white pixel(s) is obtained, their amount is multiplied with the scale that obtained from calibration process and crop yield prediction (kg/m2).
Detection of yellow paddy color that ready-to-harvest is successfully performed by processing the HSV color, which is then detected by thresholding HSV. At the time of testing with variety of paddy color, the detected paddy color is the paddy color ready-to-harvest, which is brownish yellow that represented by white pixels, and will be used then to predict its area and crop yield. Thereafter, accuracy calculation test resulting in different error levels in different paddy fields. Error in testing of this system are 3,1 %, 8,7%, 4,9% dan 248%. The highest error value is caused by excessive exposure of light, with the result that the green color on paddy is detected by the system as yellow and some areas are covered by trees that, thereby reducing paddy fields area calculation.
Keywords
Full Text:
PDFReferences
[1] Bulow, H., dan Birk, A., 2009, Fast and Robust Photommaping with an Unmanned Aerial Vehicle (UAV), Engineering and Science, Jacob Univeristy, Jerman.
[2] Pratiwi, K., dan Murti, S., H., 2012, Aplikasi Pengolahan Digital Citra Penginderaan Jauh dan Sistem Informasi Geografis untuk Pemetaan Lahan Kritis Kasus di Kabupaten Banjarnegara Provinsi Jawa Tengah, Jurnal, Universitas Gadjah Mada, Yogyakarta.
[3] Gusa, R., F., 2013, Pengolahan Citra Digital untuk Menghitung Luas Daerah Penambangan Timah, Jurnal Program Studi Teknik Elektro, Fakultas Teknik, Universitas Bangka Belitung, Bangka Belitung.
[4] Bosak, K., 2011, Secret of UAV Photomapping, Pteryx, Poland.
[5] Shofiyanti, R., 2011, Teknologi Pesawat Tanpa Awak untuk Pemetaan dan Pemantauan Tanaman dan Lahan Pertanian, Jurnal, Balai Besar Penelitian dan Pengembangan Lahan.
[6] Setiyawan, Y., 2013, Purwarupa Sistem Foto Panorama Pada Pesawat Udara Tanpa Awak, Skripsi, Jurusan Ilmu Komputer dan Elektronika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Gadjah Mada, Yogyakarta.
[7] Chen, W., Yun Q. S., dan Guorong, X., 2006, Identifying Computer Graphics Using HSV Color Model and Statistical Moments of Characteristic Functions, New Jersey Institute of Technology, Newark, NJ, USA.
[8] Hendry, J., 2004, Optimum Global Thresholding using Otsu’s Method, EE and IT of UGM, Indonesia.
[9] Crisnanto, H., 2011, Pengendalian Kualitas Cairan dalam Botol Berbasis Pengolahan Citra, Skripsi, Jurusan Teknik Industri, fakultas Teknik, Universitas Sebelas Maret, Surakarta.
[10] Yuwono, B., 2010, Image Smoothing Menggunakan Mean Filtering, Median Filtering, Modus Filtering, dan Gaussian Filtering, Jurnal, Jurusan Teknik Informatika, UPN “Veteran” , Yogyakarta.
DOI: https://doi.org/10.22146/ijeis.15258
Article Metrics
Abstract views : 3603 | views : 3806Refbacks
Copyright (c) 2016 IJEIS - Indonesian Journal of Electronics and Instrumentation Systems
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1