Dr. Mu’taz Abo Sara published a new research paper titled” An Efficient High-Speed Feature Extraction Analysis Methods of Digital Images in Social Media Platforms”.

Dr. Mu’taz Abo Sara published a new research paper titled” An Efficient High-Speed Feature Extraction Analysis Methods of Digital Images in Social Media Platforms”.

Abstract

Digital color image retrieval and recognition are very important tasks associated with digital image processing, so increasing the efficiency and accuracy of the retrieval system is a vital issue. In fact, using an image key or signature with a very small size is the solution for reducing the image-seeking time in any retrieval system. This key can be constructed from extracted image features, and this key must be small and unique. In this paper, various methods of color image feature extraction will be studied and, experimentally tested. Finally, the obtained results will be analyzed and compared to raise some facts and recommendations. In this paper, an efficient high-speed feature extraction framework for extracting features from various social media platforms. Basically, these methods are exploited in field of social media platforms such as Facebook, Twitter, Instagram.

How to cite

Alkhateeb, J. H., Rasras, R., Alqadi, Z., Sara, M. R. A., Turani, A., & Marie, R. R. (2025). An Efficient High-Speed Feature Extraction Analysis Methods of Digital Images in Social Media Platforms. In AI-Driven: Social Media Analytics and Cybersecurity (pp. 131-148). Cham: Springer Nature Switzerland.

View at publisher

https://link.springer.com/chapter/10.1007/978-3-031-80334-5_8

March 2, 2026 | Research

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