Omar Mohammed Salih

@ntu.edu.iq

Technical Engineering College of Kirkuk
Northern Technical University

Omar Mohammed Salih


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https://researchid.co/omar_alsabaawi

RESEARCH INTERESTS

Signal and Image Processing, Signal Processing Algorithms and VLSI Implementation, FPGA Implementation and Designing
12

Scopus Publications

111

Scholar Citations

5

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Efficient real-time drone mapping with visual SLAM and Python
    Hussam Rostum, Omar M. Salih, József Vásárhelyi
    Pollack Periodica, 2026
    This paper aims to develop an efficient real-time mapping workflow using a drone employing visual simultaneous localization and mapping technology, implemented using Python Programming. The control module is enhanced to guide the drone in exploring an unknown environment, enabling it to perform functionality like a LiDAR sensor but relying solely on its onboard camera to detect walls and features, and dynamically construct a map of the surrounding environment. The approach's accuracy and performance of the reconstructed map are evaluated and compared with the reference map generated using the ground truth. This work demonstrates the feasibility of using computer vision as an alternative to traditional sensing devices for real-time exploration of indoor and complex environments.
  • End-to-End Multi-Level Encoding Methods of Visual Data Compression for Robust Monocular Visual ORB-SLAM
    Omar M. Salih, József Vásárhelyi
    Acta Polytechnica Hungarica, 2025
    Simultaneous localization and mapping (SLAM) has been highly studied in the last decade.It allows the estimation of the camera pose of a mobile device and the creation of a map of the surrounding environment concurrently.Recently, Visual SLAM (VSLAM) has become the most widely used state-of-the-art technique to implement SLAM tasks due to its reduced cost, lower size, and affordability.However, the intensive computation of VSLAM systems does not fit in a wide range of limited resources and energy mobile devices.A possible solution is to split its functionality between mobile devices and the edge cloud.This solution showed the necessity for efficient visual data compression methods to be integrated within VSLAM systems.This work proposes a multi-level encoding method for visual data frame compression integrated within the monocular Oriented FAST and Rotated BRIEF-SLAM (ORB-SLAM) system.The performance results of the proposed system are compared to corresponding ORB-SLAM systems adopting the most popular classical still image compression standards; the Joint Photographic Experts Group (JPEG) and the advanced version, the JPEG 2000, in terms of reconstruction quality, robot's trajectory estimation, and computational complexity.
  • Efficient Architecture for Multi-Robot Visual SLAM Systems
    Omar M. Salih, József Vásárhelyi
    Proceedings of the 2025 26th International Carpathian Control Conference Iccc 2025, 2025
    Visual Simultaneous Localization and Mapping (VS-LAM) is a crucial algorithm used in mobile robots to determine their position relative to the encirclement environment. In multi-robot architectures, mobile robots communicate with a base station or a centralized edge device. However, the computational complexity nature of the VSLAM algorithm, due to the processing of massive visual information for tracking and mapping, poses challenges for deploying the algorithm entirely on the mobile robot. To address these limitations, this paper introduces an efficient architecture that partitions the V-SLAM framework between mobile robots and a centralized edge. This approach complies with resource limitations and optimizes energy consumption while minimizing the robot’s size and weight. In addition, the paper proposes a communication module comprising an encoding and decoding framework to obtain effective data communication between the mobile robots and the edge device. The performance of the proposed system is evaluated and compared with a corresponding architecture that employs the baseline JPEG technique in terms of trajectory accuracy, data quality, and execution time.
  • A Novel Method to Improve the Efficiency and Performance of Cloud-Based Visual Simultaneous Localization and Mapping †
    Omar M. Salih, Hussam Rostum, József Vásárhelyi
    Engineering Proceedings, 2024
    Since Visual Simultaneous Localization and Mapping (VSLAM) inherently requires intensive computational operations and consumes many hardware resources, these limitations pose challenges to implementing the entire VSLAM architecture within limited processing power and battery capacity. This paper proposes a novel solution to improve the efficiency and performance of exchanging data between the unmanned aerial vehicle (UAV) and the cloud server. First, an adaptive ORB (oriented FAST and rotated BRIEF) method is proposed for precise tracking, mapping, and re-localization. Second, efficient visual data encoding and decoding methods are proposed for exchanging the data between the edge device and the UAV. The results show an improvement in the trajectory RMSE and accurate tracking using the adaptive ORB-SLAM. Furthermore, the proposed visual data encoding and decoding showed an outstanding performance compared with the most used standard JPEG-based system over high quantization ratios.
  • Visual Data Compression Approaches for Edge-based ORB-VSLAM Systems
    Omar M. Salih, József Vásárhelyi
    Proceedings of the 2024 25th International Carpathian Control Conference Iccc 2024, 2024
    Visual Simultaneous Localization And Mapping (VSLAM) is a technique that enables robots to localize and estimate their pose by reconstructing a map structure of the surrounding environment. However, VSLAM encounters significant computational loads, resource consumption, and bandwidth constraints. Due to these issues, offloading the entire VSLAM architecture onto a mobile device could be impractical. To reduce weight, lower energy consumption, and keep the size of mobile devices small, VSLAM can be efficiently deployed by offloading computationally intensive tasks to cloud platforms. This requires efficient visual data compression methods to reduce the data load, bandwidth, and latency. This paper proposes two implementation approaches for integrating visual data compression and decompression with ORB-VSLAM systems. The proposed systems are compared to counterpart JPEG-based systems, and the results show significant improvement for both approaches.
  • An Overview of Energies Problems in Robotic Systems
    József Vásárhelyi, Omar M. Salih, Hussam Mahmod Rostum, Rabab Benotsname
    Energies, 2023
    Considering the current world trends, the most challenging issue industry is facing revolves around how to reduce the power consumption of electronic systems. Since the invention of computers, electrical energy consumption has increased dramatically; this is due to the emergence of new systems in industry. Systems like industrial robots and autonomous vehicles—including electric vehicles (EVs) and unmanned aerial vehicles (UAVs)—have had a great impact in making human life easier but have also led to higher energy consumption. At present, researchers and developers are actively seeking solutions and patents to optimize the energy consumption of the mentioned systems and generate savings, with the goal of reducing their environmental impact and improving their efficiency and effectiveness. From the literature review, papers related to energy optimization and energy consumption are considered vital, and a huge number of research publications and survey papers discuss it. This paper presents a systematic review of the classification and analysis of various methodologies and solutions that have been developed to enhance the energy performance of robotic systems, focusing on industrial robots, autonomous vehicles, and embedded systems. The aim of this research is to provide a reference point for the existing methods, techniques, and technologies that are available. It compares and evaluates different hardware and software methods related to industrial robots, autonomous vehicles, and embedded systems, highlighting the possible future perspectives in the field.
  • Second-Order Statistical Techniques for Enhancing Spectrum Sensing in Cognitive Radio
    Hussam M. Rostum, Omar M. Salih, Jozsef Vásárhelyi
    Proceedings of the 2023 24th International Carpathian Control Conference Iccc 2023, 2023
    This study explores the use of cognitive radio as a solution to the problem of radio spectrum scarcity and ineffectiveness. The focus is on spectrum sensing, a critical aspect of cognitive radio with various algorithms. The research examines a spectrum sensing algorithm based on the cyclic prefix correlation coefficient in OFDM signals(Orthogonal Frequency Division Multiplexing). The detection threshold is determined using a constant false alarm rate and a method for minimizing the average total error probability. Additionally, a formula for normalized spectrum utilization for primary and secondary users is presented. The results of the simulation show improved performance of the detector through the use of an adaptive threshold, resulting in a 6 dB increase in the probability of detection at 0.6 compared to a fixed threshold. The normalized spectrum utilization improved by approximately 5% at SNR = -12 dB for a spectrum occupancy of 0.5 and by 25% at SNR = -20dB for a spectrum occupancy of 0.7.
  • Fast Joint Image Compression-Encryption Algorithm used for 3D Reconstruction
    Omar M. Salih, Hussam M. Rostum, József Vásárhelyi, Mohammed M. Siddeq
    Proceedings of the 2023 24th International Carpathian Control Conference Iccc 2023, 2023
    This paper presents a JPEG-improved algorithm for compression and encryption of 2D structured light images applied in 3D reconstruction. The proposed method incorporates compression and encryption simultaneously to achieve a high compression ratio while adding security without affecting 3D reconstruction. The 2D structured light image is divided into 8×8 blocks, then DCT is applied for each block followed by an optimized JPEG-based quantization matrix. The resulting blocks are merged in a single matrix, and the DC coefficients in each column are subjected to first-order difference to reduce the Min-Max span for fast decoding. The decompression is accomplished reversely, and a fast sequential search method is proposed based on a conventional searching approach. The results showed achieving up to a 98% compression ratio of 2D structured light images while maintaining successful and accurate 3D reconstruction. Moreover, the execution time decreased significantly by (61%-80%).
  • Image compression for quality 3D reconstruction
    Omar M. Salih, Mohammed H. Rasheed, Mohammed M. Siddeq, Marcos A. Rodrigues
    Journal of King Saud University Computer and Information Sciences, 2022
    A 3D mesh can be reconstructed from multiple viewpoint images or from a single structured light image. Lossy compression of such images by standard techniques such as JPEG at high compression ratios lead to 3D reconstruction being adversely affected by artifacts and missing vertices. In this paper we demonstrate an improved algorithm capable of high compression ratios without adversely affecting 3D reconstruction and with minimum data loss. The compression algorithm starts by applying block DCT over the input image, and the transformed data being quantized using an optimized quantization matrix. The quantized coefficients of each block are arranged as a 1D array and saved with other block’s data in a larger matrix of coefficients. The DC coefficients are subject to a first order difference whose values are referred to as residual array. The AC coefficients are reduced by eliminating zeros and saving the non-zero values in a reduced coefficients array using a mask of 0 (for a block of zeros) and 1 (for a block of non-zeros). Finally, arithmetic coding is applied to both coefficients and residual arrays. At decompression stage, the coefficients matrix is regenerated by scanning the coefficients array and examining the headers to substitute zero and non-zero data. This matrix is then added to the residual array to obtain the original DC values. The IDCT is then applied to obtain the original image. The proposed algorithm has been tested with images of varying sizes in the context of 3D reconstruction. Results demonstrate that our proposed algorithm is superior to traditional JPEG at higher compression ratios with high perceptual quality of images and the ability to reconstruct the 3D models more effectively, both for structured light images and for sequences of multiple viewpoint images.
  • Quadtree partitioning scheme of color image based
    Ghadah Al-Khafaji, Mohammed H. Rasheed, Omar M. Salih
    Periodicals of Engineering and Natural Sciences, 2021
    Image segmentation is an essential complementary process in digital image processing and computer vision, but mostly utilizes simple segmentation techniques, such as fixed partitioning scheme and global thresholding techniques due to their simplicity and popularity, in spite of their inefficiency. This paper introduces a new split-merge segmentation process for a quadtree scheme of colour images, based on exploiting the spatial and spectral information embedded within the bands and between bands, respectively. The results show that this technique is efficient in terms of quality of segmentation and time, which can be used in standard techniques as alternative to a fixed partitioning scheme.
  • Joint image encryption and compression schemes based on hexa-coding
    Mohammed H. Rasheed, Omar M. Salih, Mohammed M. Siddeq
    Periodicals of Engineering and Natural Sciences, 2021
  • Low energy consumption in manet network
    Periodicals of Engineering and Natural Sciences, 2020

RECENT SCHOLAR PUBLICATIONS

  • Efficient real-time drone mapping with visual SLAM and Python
    H Rostum, OM Salih, J Vásárhelyi
    Pollack Periodica, 606.2025. 01493 , 2026
    2026
  • Peremhálózat alapú VSLAM keretrendszer erőforrás-korlátozott platformokhoz: An Edge Assisted VSLAM Framework for Resource Constraint Platforms
    V József, SM Omar
    Energetika-Elektrotechnika–Számítástechnika és Oktatás Multi-konferencia … , 2025
    2025
  • End-to-End Multi-Level Encoding Methods of Visual Data Compression for Robust Monocular Visual ORB-SLAM
    OM Salih, J Vásárhelyi
    Acta Polytechnica Hungarica 22 (5), 225-244 , 2025
    2025
    Citations: 1
  • Efficient Architecture for Multi-Robot Visual SLAM Systems
    OM Salih, J Vásárhelyi
    2025 26th International Carpathian Control Conference (ICCC), 1-6 , 2025
    2025
  • A novel method to improve the efficiency and performance of cloud-based visual simultaneous localization and mapping
    OM Salih, H Rostum, J Vásárhelyi
    Engineering Proceedings 79 (1), 78 , 2024
    2024
    Citations: 2
  • Visual data compression approaches for edge-based ORB-VSLAM systems
    OM Salih, J Vásárhelyi
    2024 25th International Carpathian Control Conference (ICCC), 1-6 , 2024
    2024
    Citations: 5
  • VISUAL DATA COMPRESSION FOR MACHINE VISION APPLICATIONS
    OM Salih, J Vásárhelyi
    Doktoranduszok Fóruma, 133 , 2024
    2024
  • FPGA implementation in mobile robot applications: State of the art review
    MR Hussam, MS Omar, H Noha
    Multidiszciplináris Tudományok 13 (2), 232-249 , 2023
    2023
    Citations: 4
  • An overview of energies problems in robotic systems
    J Vásárhelyi, OM Salih, HM Rostum, R Benotsname
    Energies 16 (24), 8060 , 2023
    2023
    Citations: 15
  • Quick sequential search algorithm used to decode high-frequency matrices
    MM Siddeq, MH Rasheed, OM Salih, M Rodrigues
    World Academy of Science, Engineering and Technology 17 (8), 180-187 , 2023
    2023
    Citations: 1
  • Second-order statistical techniques for enhancing spectrum sensing in cognitive radio
    HM Rostum, OM Salih, J Vásárhelyi
    2023 24th international Carpathian control conference (ICCC), 382-387 , 2023
    2023
    Citations: 2
  • Fast Joint Image Compression-Encryption Algorithm used for 3D Reconstruction
    OM Salih, HM Rostum, J Vásárhelyi, MM Siddeq
    2023 24th International Carpathian Control Conference (ICCC), 400-405 , 2023
    2023
    Citations: 4
  • Quick Sequential Search Algorithm Used to Decode High Frequency Matrices
    OM Salih
    International Journal of Electrical and Computer Engineering , 2023
    2023
  • An Overview of Energies Problems in Control and Robotic Systems
    J Vásárhelyi, OM Salih, HM Rostum, R Benotsname, AA Bouzid
    Preprints , 2022
    2022
  • Image compression for quality 3D reconstruction
    OM Salih, MH Rasheed, MM Siddeq, MA Rodrigues
    Journal of King Saud University-Computer and Information Sciences 34 (5 … , 2022
    2022
    Citations: 12
  • Quadtree partitioning scheme of color image based
    GK AL-Khafaji, MH Rasheed, OM Salih
    Periodicals of Engineering and Natural Sciences 9 (2), 1073-1085 , 2021
    2021
    Citations: 1
  • Joint image encryption and compression schemes based on hexa-coding
    MH Rasheed, OM Salih, MM Siddeq
    Periodicals of Engineering and Natural Sciences 9 (2), 569-580 , 2021
    2021
    Citations: 17
  • Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm
    MH Rasheed, OM Salih, MM Siddeq, MA Rodrigues
    Array 6, 100024 , 2020
    2020
    Citations: 43
  • Low energy consumption in manet network
    MA Mustafa, MH Rasheed, OM Salih
    Periodicals of Engineering and Natural Sciences (PEN) 8 (2), 904-915 , 2020
    2020
    Citations: 3
  • A Low Complexity Slm Scheme for Papr Reduction of OFDM Signals
    OM Salih, AI Siddiq
    Diyala Journal of Engineering Sciences 10 (3), 63-74 , 2017
    2017
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm
    MH Rasheed, OM Salih, MM Siddeq, MA Rodrigues
    Array 6, 100024 , 2020
    2020
    Citations: 43
  • Joint image encryption and compression schemes based on hexa-coding
    MH Rasheed, OM Salih, MM Siddeq
    Periodicals of Engineering and Natural Sciences 9 (2), 569-580 , 2021
    2021
    Citations: 17
  • An overview of energies problems in robotic systems
    J Vásárhelyi, OM Salih, HM Rostum, R Benotsname
    Energies 16 (24), 8060 , 2023
    2023
    Citations: 15
  • Image compression for quality 3D reconstruction
    OM Salih, MH Rasheed, MM Siddeq, MA Rodrigues
    Journal of King Saud University-Computer and Information Sciences 34 (5 … , 2022
    2022
    Citations: 12
  • Visual data compression approaches for edge-based ORB-VSLAM systems
    OM Salih, J Vásárhelyi
    2024 25th International Carpathian Control Conference (ICCC), 1-6 , 2024
    2024
    Citations: 5
  • FPGA implementation in mobile robot applications: State of the art review
    MR Hussam, MS Omar, H Noha
    Multidiszciplináris Tudományok 13 (2), 232-249 , 2023
    2023
    Citations: 4
  • Fast Joint Image Compression-Encryption Algorithm used for 3D Reconstruction
    OM Salih, HM Rostum, J Vásárhelyi, MM Siddeq
    2023 24th International Carpathian Control Conference (ICCC), 400-405 , 2023
    2023
    Citations: 4
  • Low energy consumption in manet network
    MA Mustafa, MH Rasheed, OM Salih
    Periodicals of Engineering and Natural Sciences (PEN) 8 (2), 904-915 , 2020
    2020
    Citations: 3
  • A novel method to improve the efficiency and performance of cloud-based visual simultaneous localization and mapping
    OM Salih, H Rostum, J Vásárhelyi
    Engineering Proceedings 79 (1), 78 , 2024
    2024
    Citations: 2
  • Second-order statistical techniques for enhancing spectrum sensing in cognitive radio
    HM Rostum, OM Salih, J Vásárhelyi
    2023 24th international Carpathian control conference (ICCC), 382-387 , 2023
    2023
    Citations: 2
  • End-to-End Multi-Level Encoding Methods of Visual Data Compression for Robust Monocular Visual ORB-SLAM
    OM Salih, J Vásárhelyi
    Acta Polytechnica Hungarica 22 (5), 225-244 , 2025
    2025
    Citations: 1
  • Quick sequential search algorithm used to decode high-frequency matrices
    MM Siddeq, MH Rasheed, OM Salih, M Rodrigues
    World Academy of Science, Engineering and Technology 17 (8), 180-187 , 2023
    2023
    Citations: 1
  • Quadtree partitioning scheme of color image based
    GK AL-Khafaji, MH Rasheed, OM Salih
    Periodicals of Engineering and Natural Sciences 9 (2), 1073-1085 , 2021
    2021
    Citations: 1
  • A Low Complexity Slm Scheme for Papr Reduction of OFDM Signals
    OM Salih, AI Siddiq
    Diyala Journal of Engineering Sciences 10 (3), 63-74 , 2017
    2017
    Citations: 1
  • Efficient real-time drone mapping with visual SLAM and Python
    H Rostum, OM Salih, J Vásárhelyi
    Pollack Periodica, 606.2025. 01493 , 2026
    2026
  • Peremhálózat alapú VSLAM keretrendszer erőforrás-korlátozott platformokhoz: An Edge Assisted VSLAM Framework for Resource Constraint Platforms
    V József, SM Omar
    Energetika-Elektrotechnika–Számítástechnika és Oktatás Multi-konferencia … , 2025
    2025
  • Efficient Architecture for Multi-Robot Visual SLAM Systems
    OM Salih, J Vásárhelyi
    2025 26th International Carpathian Control Conference (ICCC), 1-6 , 2025
    2025
  • VISUAL DATA COMPRESSION FOR MACHINE VISION APPLICATIONS
    OM Salih, J Vásárhelyi
    Doktoranduszok Fóruma, 133 , 2024
    2024
  • Quick Sequential Search Algorithm Used to Decode High Frequency Matrices
    OM Salih
    International Journal of Electrical and Computer Engineering , 2023
    2023
  • An Overview of Energies Problems in Control and Robotic Systems
    J Vásárhelyi, OM Salih, HM Rostum, R Benotsname, AA Bouzid
    Preprints , 2022
    2022