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All Journal Al-Jabar : Jurnal Pendidikan Matematika International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Junoh, Ahmad Kadri bin
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Education Mathematics Physics

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White blood cell segmentation by using vector color approach Abdurrazzaq, Achmad; Junoh, Ahmad Kadri bin; Yulianto, Ilyasa Pahlevi Reza
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 1, No 1 (2023): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v1i1.158

Abstract

White blood cells play an important role in protecting the body from various types of diseases, therefore blood tests are done to determine a person’s disease. Diagnosis of blood diseases is done by analyzing and counting the white blood cells in the blood. Optimal calculations and analysis of white blood cell are important, so research on white blood cell detection is a rapidly growing topic. Many detection methods are proposed using the existing segmentation techniques. In this paper, the detection method is proposed using vector operation approach instead general segmentation technique. From the experiments performed, it is shown that the proposed method can detect white blood cells on smear images. Further, this method extracts the nucleus from white blood cells well.
Implementation of interpolation method in reconstructing damaged satellite image caused by impulse noise Riawan Syahrul Haz, Habban; Abdurrazzaq, Achmad; Junoh, Ahmad Kadri bin; Syazali, Muhamad
Al-Jabar: Jurnal Pendidikan Matematika Vol 14 No 2 (2023): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v14i2.14069

Abstract

Background: Images are extensively utilized in fields such as engineering, health, and defense. During transmission, these images often lose quality due to noise interference.Aim: The primary objective of this study is to develop a method to effectively reduce salt and pepper noise, a common issue in image transmission, and restore images to their original state.Method: To achieve this, we propose using a numerical approach based on the interpolation method, specifically designed to address the noise reduction challenge.Result: Experimental application of the interpolation method on various images demonstrated that it significantly enhances the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) values, especially for images with low to medium noise density.Conclusion: Compared to other methods, our interpolation-based approach shows superior performance in reducing salt and pepper noise in images, making it a promising solution for image restoration in various applications.
Bibliometrix research of noise removal techniques in digital images for defense Al Husein, Fulkan Kafilah; Al Habsy, Muhammad Yusuf; Christi, Damaris Nugrahita; Hutagaol, Agnes Emanuela; Junoh, Ahmad Kadri bin
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol 3, No 1 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Natio
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i1.463

Abstract

In modern defense applications, the accuracy and clarity of digital images are crucial, especially for tasks like surveillance, reconnaissance, and intelligence gathering. However, noise introduced during image acquisition or transmission significantly degrades image quality. This paper presents a comprehensive review of various noise removal techniques employed in digital image processing for defense systems. The review focuses on both linear and non-linear methods, including matrix decomposition, hybrid deep learning, Generative Adversarial Networks (GANs), and trimming filters. Emphasis is placed on the effectiveness of each technique in enhancing image quality while preserving critical details. The use of linear and non-linear methods such as deep learning-based approaches is shown to outperform traditional linear filters in handling complex noise patterns, particularly in scenarios requiring precise object detection and image restoration. The paper highlights a comprehensive overview of the researched literature and shows the latest trends and developments in the field. Finally, recommendations for future research and the development of more robust noise reduction methods are provided, aiming to improve operational effectiveness in defense applications.
Co-Authors Abdurrazzaq, Achmad Al Habsy, Muhammad Yusuf Al Husein, Fulkan Kafilah Christi, Damaris Nugrahita Hutagaol, Agnes Emanuela Muhamad Syazali Riawan Syahrul Haz, Habban Yulianto, Ilyasa Pahlevi Reza