The Evolution of Image Processing: A Critical Overview of Modern Trends and Key Technologies
Shakir Amjad1, Umar Daraz2
1Shakir Amjad, Department of Bionic Engineering, College of Biological and Agricultural Engineering, Jilin University, China.
2Umar Daraz, College of Agronomy, Gansu Agricultural University, Lanzhou, China.
Manuscript received on 29 March 2026 | Revised Manuscript received on 04 April 2026 | Manuscript Accepted on 15 April 2026 | Manuscript published on 30 April 2026 | PP: 1-3 | Volume-13 Issue-4, April 2026 | Retrieval Number: 100.1/ijies.C104106030426 | DOI: 10.35940/ijies.C1041.13040426
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image processing has emerged as a critical tool across diverse domains, including agriculture, healthcare, industrial automation, and robotics. This review highlights the major technologies employed in image analysis and explores their methodologies, strengths, and practical applications. Approaches range from traditional image processing techniques to advanced machine learning and deep learning frameworks, as well as specialised modalities such as hyperspectral and 3D imaging. Each method provides distinct advantages, from simple filtering and segmentation to real-time object detection and high-precision phenotyping, enabling more accurate and efficient analysis across various fields.
Keywords: Image Processing, Image Analysis, Machine Learning, Technology Review
Scope of the Article: Agricultural Engineering