IMPROVING THE IMAGE OF A BANANA USING THE OPENING AND CLOSING METHOD

Siti Fauziah; Nita Merlina; Nissa Almira Mayangky; Muhamad Hasan; Nabil Ali Fahrurrozi4; Yogi Yosua Panjaitan; Ananta Kusuma Putra

doi:10.33480/pilar.v21i1.5968

Authors

Siti Fauziah Universitas Nusa Mandiri
Nita Merlina Universitas Nusa Mandiri
Nissa Almira Mayangky
Muhamad Hasan Universitas Nusa Mandiri
Nabil Ali Fahrurrozi4
Yogi Yosua Panjaitan
Ananta Kusuma Putra

DOI:

https://doi.org/10.33480/pilar.v21i1.5968

Keywords:

banana image, closing method, image processing, image quality enhancement, opening method

Abstract

One significant technique in image processing is morphological image operations, which include methods such as opening and closing. This research explores the application of the opening and closing methods in improving the quality of banana images. The Opening process effectively reduces noise and eliminates small, unwanted details, improving the clarity of the image. However, the Closing process presents some challenges, particularly in altering the natural texture of the banana and blurring fine lines. Careful adjustments are necessary to avoid reducing the visual quality of the image. The study begins with pre-processing steps such as image cleaning and contrast adjustment to enhance the image clarity. The Opening operation, using mathematical morphology and a structural element, removes unwanted small elements from the image, making fine lines and textures more visible for further analysis. The Closing operation, applied after Opening, fills small gaps and connects separated parts of the banana image, restoring the original structure and maintaining image continuity. The combined application of opening and closing methods significantly enhances the quality of banana images by improving clarity, preserving structural integrity, and optimizing overall visual appearance.

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References

Apridiansyah, Y., Toyib, R., & Wijaya, A. (2022). Metode Otsu dan Mathematical Morphology Dalam Segmentasi Region Karakter Plat Nomor Kendaraan. Journal of Applied Computer Science and Technology, 3(1), 134–143. https://doi.org/10.52158/jacost.v3i1.277

Arnita, Marpaung, F., Aulia, F., Suryani, N., & Nabila, R. C. (2022). COMPUTER VISION DAN PENGOLAHAN CITRA DIGITAL (Pertama). Surabaya: Pustaka Aksara.

Buyukkinaci, M. (2019). Fruit Images for Object Detection. Retrieved from Kaggle website: https://www.kaggle.com/datasets/mbkinaci/fruit-images-for-object-detection/data

Dijaya, R. (2023). Buku Ajar Pengolahan Citra Digital. Sidoarjo: UMSIDA Press.

Fitriyah, H., & Wihandika, R. C. (2021). Dasar-Dasar Pengolahan Citra Digital (Pertama). Malang: UB Press.

Hou, Y., Li, Q., Zhang, C., Lu, G., Ye, Z., Chen, Y., … Cao, D. (2021). The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis. Engineering, 7(6), 845–856. https://doi.org/10.1016/j.eng.2020.07.030

Khairullah, & Putra, E. D. (2021). Identifikasi Kematangan Cabai Menggunakan Operasi Morfologi ( Opening dan Closing ) dan Metode Backpropagation. SISTEMASI:Jurnal Sistem Informasi, 10(1), 96–105. https://doi.org/10.32520/stmsi.v10i1.1094

Kumar, A., Chakravarty, S., Gupta, M., Baig, I., & Albreem, M. A. (2022). Implementation of Mathematical Morphology Technique in Binary and Grayscale Image. Advance Concepts of Image Processing and Pattern Recognition, 203–212. https://doi.org/10.1007/978-981-16-9324-3_11

Neto, U. B. (2024). Fundamentals of Pattern Recognition and Machine Learning (1st ed.). Switzerland: Springer Cham.

Rumandan, R. J., Nuraini, R., Sadikin, N., & Rahmanto, Y. (2022). Klasifikasi Citra Jenis Daun Berkhasiat Obat Menggunakan Algoritma Jaringan Syaraf Tiruan Extreme Learning Machine. 4(1), 145−154. https://doi.org/10.47065/josyc.v4i1.2586

Salvi, M., Acharya, U. R., Molinari, F., & Meiburger, K. M. (2021). The impact of pre- and post-image processing techniques on deep learning frameworks : A comprehensive review for digital pathology image analysis. Computers in Biology and Medicine, 128, 104129. https://doi.org/10.1016/j.compbiomed.2020.104129

Sari, L. A., Maulita, Y., & Ambarita, I. (2021). Image Smoothing Pada Citra Ultrasonografi (USG) Dengan Metode Harmonic Mean Filter. ALGORITMA: Jurnal Ilmu Komputer Dan Informatika, 5(2), 113–124. http://dx.doi.org/10.30829/algoritma.v5i2.10588

Setyansyah, R., Siregar, Y. S., & Khairani, M. (2021). Noise Removal Pada Citra Digital Dengan Menggunakan Metode Active Contour. ALGORITMA: Jurnal Ilmu Komputer Dan Informatika, 5(2), 134–142. http://dx.doi.org/10.30829/algoritma.v5i2.10700

Sitinjak, S. (2020). Pengujian Modifikasi Kernel Konvolusi Untuk Penajaman dan Penghalusan Citra Berwarna. Faktor Exacta, 13(2), 96–105. https://doi.org/10.30998/faktorexacta.v13i2.6585

Situmorang, E. P. S., Hasibuan, N. A., & Siregar, S. R. (2022). Implementasi Pengurangan Noise Pada Citra Rontgen Paru Menggunakan Metode Filter Adaptive-Hierarchical. Resolusi : Rekayasa Teknik Informatika Dan Informasi, 2(3), 116–120. https://doi.org/10.30865/resolusi.v2i3.308

Soedjono, S. (2019). Bersama Menyigi dan Meneroka Fotografi, Media, dan Seni. Yogyakarta: Badan Penerbit ISI Yogyakarta.

Sumijan, & Purnama, P. A. W. (2021). Teori dan Aplikasi Pengolahan Citra Digital Penerapan dalam Bidang Citra Medis (Pertama). Sumatra Barat: Insan Cendikia Mandiri.

Supiyanto, & Suparwati, T. (2021). Perbaikan Citra Menggunakan Metode Contrast Stretching. Jurnal Siger Matematika, 02(01), 13–18. https://doi.org/10.23960/jsm.v2i1.2743

Trianto, G. A., Sinaga, F. J., Marzuki, M. F., & Qorni, Q. Al. (2022). Operasi Opening dan Closing pada Pengolahan Citra Digital Menggunakan Matlab. MDP Student Conference 2022, 104–110.