Hamdani Hamdani
Papers
2
Total Citations
73
H-Index
2
About
Hamdani Hamdani is a leading researcher in agricultural image processing and computer vision, with a focus on automating fruit detection and segmentation for precision agriculture. His work centers on developing robust algorithms that enable machines to identify and analyze crops, directly supporting advancements in harvesting robotics and maturity assessment. Hamdani’s most influential contribution, the 2019 paper “Automatic image segmentation of oil palm fruits by applying the contour-based approach,” has garnered 57 citations, establishing a foundational method for segmenting complex, clustered fruits. He further advanced the field with his 2022 study on tomato segmentation, which integrates K-means clustering with edge detection to achieve accurate fruit boundary delineation. This work, cited 16 times, addresses a critical step in robotic harvesting systems by improving the reliability of fruit identification under varying conditions. Hamdani’s research bridges the gap between theoretical image processing techniques and practical agricultural applications, offering scalable solutions for crop monitoring and automation. His contributions are particularly notable for tackling the challenges of segmenting non-uniform, overlapping fruits, making his methods valuable for both researchers and engineers developing smart farming technologies.
Research Focus
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Top Papers
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