Pengembangan Algoritma Image Processing untuk Menduga Hasil Panen Padi

  • Made Arya Bhaskara Putra Prodi. Teknik Pertanian, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia
  • I Made Anom S. Wijaya Prodi. Teknik Pertanian, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia
  • Yohanes - Setiyo Prodi. Teknik Pertanian, Fakultas Teknologi Pertanian, Universitas Udayana, Badung, Bali, Indonesia

Abstract

The aims of this research were to develop image processing algorithm that can be used for rice yield estimation. This research consist of: 1) image acquisition, 2) image analysis with Adobe Photoshop Cs 4 and MATLAB R2009B, and 3) make the algorithm that suitable for rice yield estimation. This research was testing three method of image processing, i.e. manual pre-processing, thresholding method, and shape of Structuring Elements (SE). Forming algorithm was done by analyzing image yield and be compare with real image. More like image yield with real image, then this method was suitable for doing rice image analysis. The result of analysis showed that process of rice image analysis have to be started with manual pre-processing, using custom thresholding method, and morphology with SE shape disk. The result image of the algorithm showed the most appropriate grain image with real image, and there’s no more image that identified as a grain. Based on number of pixel, the image yield of this method is 117.407 pixel. In conclusion, the algorithm for estimation of rice yield, consist of: image acquisition, manual pre-processing, gray scaling, thresholding custom, morphology with SE shape disk, image resize, and calculation of the number of pixel grain.

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Published
2015-02-01
How to Cite
PUTRA, Made Arya Bhaskara; S. WIJAYA, I Made Anom; SETIYO, Yohanes -. Pengembangan Algoritma Image Processing untuk Menduga Hasil Panen Padi. Jurnal BETA (Biosistem dan Teknik Pertanian), [S.l.], v. 3, n. 1, feb. 2015. ISSN 2502-3012. Available at: <https://ojs.unud.ac.id/index.php/beta/article/view/19737>. Date accessed: 01 oct. 2020.
Section
Articles

Keywords

image processing analysis, image processing algorithm, structuring elements, custom thresholding, numbers of grain pixel.