The International University for Science and Technology participates in the International Conference on Decision-Assisted Sciences and their Applications in Bahrain.

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  • The International University for Science and Technology participates in the International Conference on Decision-Assisted Sciences and their Applications in Bahrain.

Dr. Mahmoud Mahfouri, from the Department of Computer and Information Technology at the International University for Science and Technology, participated in the 2024 International Conference on Decision-Assisted Sciences and their Applications (DASA), held in Manama, Bahrain, from December 11-12, 2024. He and a team of other researchers presented five research papers, which were published at the conference. The first was titled:

“An Analytical Study of the Characteristics and Parameters of the Non-Angle Iris Image versus a Deep Learning Model.”

This paper presents an analytical study and a technique for extracting the features of a common case of images of the iris called off-angle iris which was taken for person’s identification systems. The main problem when using biological iris measurements to identify the persons is the difficulty of identifying and extracting features of the iris. This problem is increasing when dealing with off-angle iris and it leads to decreased system accuracy and increased system rate error. In return, all the transfer learning techniques face difficulties in the case of heavily degraded data and partially occluded, and off-angle. A new method has a whole new methodology to deal with the image as it is without transformation processes. A new algorithm has been included for extracting features of the iris through the pupil switching points. The most discriminating points of the iris depend on the biological human eye statistics and analytical study. It has been trained and tested on the common images of the off-angle iris database so-called: “CASIA Iris 1.0”. It has been implemented in the MATLAB environment. The results showed the efficiency of this technique, high precision and more importantly low failed acceptance rate. It emphasized that it is adaptive as well as efficiency improvement of the system.

Published in: 2024 International Conference on Decision Aid Sciences and Applications (DASA)