Sahar A. El Rahman

Work place: Faculty of Engineering-Shoubra / Electronics, Computers Systems & communication - Electrical Department, Cairo, Egypt



Research Interests: Computer systems and computational processes, Computer Vision, Robotics, Image Compression, Image Manipulation, Computer Networks, Image Processing


Sahar Abd El_Rahman was born in Cairo, Egypt, B.Sc. Electronics, Computer Systems & communication, Electrical Engineering Department. Benha University, Shoubra Faculty of Engineering, Cairo-Egypt. M.Sc. in an AI Technique Applied to Machine Aided Translation, Electronic Engineering, Electrical Engineering Department, Benha University, Shoubra Faculty of Engineering, Cairo-Egypt, May2003. PHD. in Reconstruction of High-Resolution Image from a Set of Low-Resolution Images, Electronic Engineering, Electrical Engineering Department, Benha University, Shoubra Faculty of Engineering, Cairo-Egypt in Jan2008.
She is ASSISTANT PROFESSOR from 2011 till now at Princess Nourah Bint Abdulrahman University/Department of Computer Science, College of Computer and Information System. Also, She is ASSISTANT PROFESSOR from 2008 till now at Electronics & communication, and Computer Systems, Electrical Engineering Department, Faculty of Engineering, Shoubra,, Benha University, Cairo, Egypt. She was a LECTURE in the same location from 2003 and INSTRUCTOR in the same location in 1998. Her research interests include computer vision, digital image processing, Signal processing, information security and cloud computing.
Dr. Sahar A. El_Rahman is a member of IACSIT (International Association of Computer Science and Information Technology) since 2013.A member of IAENG (International Association of Engineers) since 2011.A member of the Egyptian Engineers’ Syndicate since 1997.

Author Articles
Course and Student Management System Based on ABET Computing Criteria

By Sahar A. El Rahman Sahar S. Shabanah

DOI:, Pub. Date: 8 May 2016

Accreditation is considered as one of the major aspects of ABET, where educational institutions continuously develop the quality of academic programs to achieve it. For the most part of this continuous development needs, the programs determine definite and measured objectives for their students, evaluate their efforts to achieve these objectives, and amend their programs based on the results of that assessment. In addition to providing educational institutions an organized strategy to appraise and develop their programs. The primary focal point to prepare for accreditation is the learning objectives and program outcomes assessment. So, College of Computer and information Sciences (CCIS) at Princess Nourah Bint Abdulrahman (PNU) needs to fulfill ABET criteria to achieve the outcomes. So, CCIS need a system to achieve course assessment matrix without wasting the time and efforts. This system will help the staff members in identifying student learning objectives that are expected to achieve as well as to identify assessment tools and evaluation feedback for each topic. This paper describes Course and Student Management System (CSMS) established to address a course assessment matrix, and help achieve department-stated objectives. Whereas, CSMS is a web based system provides many features to facilitate the creation of articulation matrix, course assessment based on students learning objectives, the student's evaluation and tracking attendance of students. This system is considered as a new method of creating the course assessment matrix that will help the department head, instructors and course coordinator. It is user friendly and interactive interface, saving the time and efforts.

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Development of Quality Assurance System for Academic Programs and Courses Reports

By Sahar A. El Rahman Bashayer A. Al-Twaim

DOI:, Pub. Date: 8 Jun. 2015

This paper aims to review a proposed Quality Assurance system (QA) which suggests developing the internal quality assurance system of academic programs at the College of Computer and Information Sciences (CCIS), Princess Nourah Bint Abdulrahman University (PNU), Riyadh, Kingdom of Saudi Arabia (KSA), by replacing the existing paper-based QA System into a web-based system. In general, the QA system will work as: providing users the required NCAAA (National Commission for Academic Accreditation and Assessment) reports' forms to be filled. Then, the proposed QA system will gather forms and generates completed reports. At the same time, it provides them to the decision makers. The proposed QA system will allow decision makers to approve reports and view gathered information in many views in which will facilitate the making decision processes in continuing improvement of the educational processes and outcomes. Also, QA system can be extended and applied to other PNU colleges. After that, it can be applied to all KSA universities.

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A Comprehensive Image Steganography Tool using LSB Scheme

By Sahar A. El Rahman

DOI:, Pub. Date: 8 May 2015

As a consequence of the fact, transmitting data has been fast and easy these days due to the development of the Internet. Where internet is the most important medium for confidential and non-confidential communications. Security is the major matter for these communications and steganography is the art of hiding and transmitting secret messages through carriers without being exposed. This paper presents a secured model for communication using image steganography. The main concern is to create a Java-based tool called IMStego that hides information in images using Least Significant Bit (LSB) algorithm (1-LSB) and modified Least Significant one Bit algorithm, i.e. Least Significant 2 Bits algorithm (2-LSB). IMStego is a more comprehensive security utility where it provides user-friendly functionality with interactive graphical user interface and integrated navigation capabilities. It provides the user with two operations, which are hiding secret data into images and extracting hidden data from images using 1-LSB or 2-LSB algorithm. IMStego tool hides secrete information in color static images with formats BMP and PNG. 

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Supervised Classification Approaches to Analyze Hyperspectral Dataset

By Sahar A. El Rahman Wateen A. Aliady Nada I. Alrashed

DOI:, Pub. Date: 8 Apr. 2015

In this paper, Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) classification approaches were used to classify hyperspectral image of Georgia, USA, using Environment of Visualizing Images (ENVI). It is a software application used to process and analyze geospatial imagery. Spatial, spectral subset and atmospheric correction have been performed for SAM and SID algorithms. Results showed that classification accuracy using the SAM approach was 72.67%, and SID classification accuracy was 73.12%. Whereas, the accuracy of SID approach is better than SAM approach. Consequently, the two approaches (SID and SAM) have proven to be accurately converged in classification of hyperspectral image of Georgia, USA.

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