Taif Ali Alobaidi

Faculty: Engineering
Position: None
Title: Lecturer
Qualifications: Ph. D.
Email: [email protected]

   



Not available!!!


PhD in Communications Engineering, Department of Electrical and Computer Engineering, University of Central Florida, Florida, USA (2018); Master of Science in Electronics and Communications Engineering from Al- Mustansiriya University, College of Engineering, Electrical Engineering Department, Baghdad, Iraq (2009);Bachelor of Science in Electrical Engineering from Al- Mustansiriya University, College of Engineering, Electrical Engineering Department, Baghdad, Iraq, ranked 2nd in class (2006)

2009-2012, Assistant Lecturer, Baghdad, Iraq, Prepared and presented lectures for undergraduate engineering students, Active IEEE member in several societies


  • T. Alobaidi and W. B. Mikhael, "Face Recognition Technique in Transform Domains," 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), Springfield, MA, USA, 2020, pp. 848-851, doi: 10.1109/MWSCAS48704.2020.9184690. 
  • Alobaidi, T., Mikhael, W. (2024). Face Identification System in Transform Domains Over Secure Communication Channel. In: Al-Bakry, A.M., et al. New Trends in Information and Communications Technology Applications. NTICT 2023. Communications in Computer and Information Science, vol 2096. Springer, Cham. https://doi.org/10.1007/978-3-031-62814-6_10
  • Alobaidi, T. (2024). Successive Transforms Residual-Based Signal Representation for Biometric Identification Application. IAR Journal of Engineering and Technology, 5(2), 1-8.
  • Alobaidi, T., Mikhael, W. An adaptive steganography insertion technique based on wavelet transform. J. Eng. Appl. Sci. 70, 144 (2023). https://doi.org/10.1186/s44147-023-00300-x

Alobaidi, T., & Mikhael, W. (2024). An Adaptive Steganography Insertion Technique Based on Cosine Transform.

  • Taif Alobaidi and Wasfy B. Mikhael,” A Transform Domain Implementation of Sparse Representation Method for Robust Face Recognition”, Published the Circuits, Systems, and Signal Processing International Journal, 2019, Volume 38, Issue 9, pp 4302-4313. DOI: 10.1007/s00034-019-01099-w. 

Taif Alobaidi and Wasfy B. Mikhael,” A Mixed Nonorthogonal Transforms Representation for Face Recognition”, Published the Circuits, Systems, and Signal Processing International Journal, April 2019, Volume 38, Issue 4, pp 1684–1694. DOI: 10.1007/s00034-018-0931-4. First Online: 31 August 2018.


Taif Alobaidi and Wasfy B. Mikhael,” A Wavelet Domain Implementation of Sparse Representation Method for Face Recognition”, presented at the IEEE 61th International Midwest Symposium on Circuits and Systems (MWSCAS), 5 - 8 August 2018, Caesars Windsor Hotel, Windsor, ON, Canada. DOI:  10.1109/MWSCAS.2018.8623943 .


Taif Alobaidi and Wasfy B. Mikhael,” A modified discriminant sparse representation method for face recognition”, presented at  2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), 8 - 10 January 2018, University of Nevada Las Vegas, Las Vegas, Nevada, USA. DOI: 10.1109/CCWC.2018.8301679.


Taif Alobaidi and Wasfy B. Mikhael,”  Face recognition system based on features extracted from two domains”, presented at the  IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 6-9 Aug. 2017, Boston, MA, USA.  DOI: 10.1109/MWSCAS.2017.8053089


Taif Alobaidi and Wasfy B. Mikhael,” Two-Step Feature Extraction in A Transform Domain for Face Recognition”, presented at the 7th IEEE Annual Computing and Communication Workshop and Conference (CCWC), 9 - 11 January 2017, Las Vegas, Nevada, USA. DOI: 10.1109/CCWC.2017.7868381


Taif Alobaidi, George K. Atia, and Wasfy B. Mikhael,” Face Recognition Using the Principal Components of the Scatter Matrix in the Frequency Domain”, presented at the IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS) 16-19 October 2016, Abu Dhabi, United Arab Emirates (UAE). DOI: 10.1109/MWSCAS.2016.7869955.


Taif Al Obaidi, Ahmed Aldhahab, and Wasfy B. Mikhael, “Employing Vector Quantization in A Transform Domain for Facial Recognition”, published in IEEE conference proceedings, presented at the 7th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference, 20 - 22 October 2016, New York City, USA. DOI: 10.1109/UEMCON.2016.7777823