Image segmentation and feature extraction research in Saudi Arabia: Progress, challenges, and future directions (1995–2024)

Jamil A. M. Saif ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 2, 2286-2306

Abstract: Image segmentation is an essential process and serves as a foundation on which feature extraction is based. There is also rapid development in this field in Saudi Arabia, which should be accompanied by a review study to trace the evolution of the field and its emerging aspects. In this regard, VOSviewer and Biblioshiny are used to develop a comprehensive study of academic research publications on image segmentation for feature extraction in Saudi Arabia between 1995 and 2024, utilizing Scopus data. This is corroborated by findings that there has been an advancing trend in publication output within the last ten years—a clear manifestation of enhanced research activity in this area. Fundamental terms such as ‘deep learning,’ ‘convolutional neural networks,’ and ‘edge detection’ were observed to be among the most preferred, pointing to the high utility of machine learning in current research work. The research demonstrates that there are effective networks of collaboration and partnerships between the top Saudi authors and Saudi institutions that characterize the research environment in the country. As image segmentation research continues to evolve, this bibliometric study provides information on its evolution in Saudi Arabia, fueled by machine learning and the synergy of disciplines.

Keywords: Deep learning; Feature extraction; Image segmentation; Object detection; Review. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:9:y:2025:i:2:p:2286-2306:id:5071

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