Image Segmentation of Red Onion Leaves Using Canny Edge Detection Method
Abstract
One important plant in agriculture is red onion, and red onion leaves are often observed to evaluate their health and development. This research aims to develop a method for segmenting images of red onion leaves using the Canny edge detection method. The Canny edge detection method is well-known for its ability to accurately and sharply detect edges in images. This method automatically determines optimal values based on image analysis. It is applied to a dataset of red onion leaf images that have significant variations in intensity, background, and brightness levels. The segmentation results are evaluated using evaluation metrics such as MSE and PSNR. The research findings indicate that the Otsu thresholding method provides good segmentation results with a PSNR of 51.4891 and MSE of 0.4590. This research is expected to broaden the understanding of image analysis in the context of agriculture and provide support for the development of more efficient and sustainable agricultural technologies.
References
A. Kadir and A. Susanto, Teori dan Aplikasi Pengolahan Citra. Yogyakarta, Indonesian: Andi, 2013.
Tambunan, T. A. (2019). IMPLEMENTASI METODE CANNY PADA SEGMENTASI CITRA DIGITAL MATLAB 2016. Kumpulan
Lankton, V. D. A. N., & Soepomo, P. (2013). ANALISIS PERBANDINGAN TEKNIK SEGMENTASI CITRA DIGITAL MENGGUNAKAN METODE LEVEL-SET CHAN &, 1, 232–240
Wardana, A. K., Febriani, A. S., & Saleh, M. R. (2021). Sistem Absensi dan Monitoring Marketing Arteri Pondok Indah Divisi Used Car Menggunakan Metode Algoritma K-Nearest Neighbor dan Naive Bayes pada PT BCA Finance. Respati, 16(2), 129-137.
Arbi, M. (2011). Faktor-faktor yang mempengaruhi petani melakukan tunda jual di Kecamatan Sanden Kabupaten Bantul. Jurnal Sosial Ekonomi Pertanian (J-SEP), 5(3), 39-44.
Eskicioglu, A.M., dan Fisher, P.S. 1995. Image Quality Measures and Their Performance. IEEE Transactions on Communications. Vol.43,No.12: 2959-2965. Diakses pada url : http://ieeexplore.ieee.org/document/ 477498
Prabowo, D. A., & Abdullah, D. (2018). Deteksi dan perhitungan objek berdasarkan warna menggunakan Color Object Tracking. Pseudocode, 5(2), 85-91.
Sukatmi, S. (2017). Perbandingan Deteksi Tepi Citra Digital dengan Menggunakan Metode Prewitt, Sobel dan Canny. KOPERTIP: Jurnal Ilmiah Manajemen Informatika Dan Komputer, 1(1), 1-7.
Tambunan, T. A. (2019). IMPLEMENTASI METODE CANNY PADA SEGMENTASI CITRA DIGITAL MATLAB 2016. Kumpulan
Utami, A. T., & Diah Priyawati, S. T. (2017). Implementasi metode otsu thresholding untuk segmentasi citra daun (Doctoral dissertation, Universitas Muhammadiyah Surakarta).
Copyright (c) 2024 Taufik Rizki Kurniawan, Danar Putra Pamungkas
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Copyright on any article is retained by the author(s).
- The author grants the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
- The article and any associated published material is distributed under the Creative Commons Attribution-ShareAlike 4.0 International License
