Omar Mohammed Salih -

Lecturer

Omar Mohammed Salih

Research Interests

Gender	MALE
Place of Work	Technical Engineering College/ Kirkuk
Position	Lecturer
Qualification	Master
Speciality	Computer Engineering
Email	omar.alsabaawi@ntu.edu.iq
Phone	+9647702543925
Address	Kirkuk, Iraq, Kirkuk, Kirkuk, Iraq

Academic Links

Publications

End-to-End Multi-Level Encoding Methods of Visual Data Compression for Robust Monocular Visual ORB-SLAM

May 21, 2025

Journal Acta Polytechnica Hungarica

publisher Obuda University

DOI https://doi.org/10.12700/APH.22.5.2025.5.12

Issue 5

Volume 22

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.

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A Novel Method to Improve the Efficiency and Performance of Cloud-Based Visual Simultaneous Localization and Mapping

Nov 11, 2024

Journal Engineering Proceedings

publisher MDPI

DOI https://doi.org/10.3390/engproc2024079078

Issue 1

Volume 79

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.

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FPGA implementation in mobile robot applications: State of the Art Review

Dec 20, 2023

Journal Multidisciplinary Sciences

publisher University of Miskolc

DOI https://doi.org/10.35925/j.multi.2023.2.21

Issue 2

Volume 13

Field-programmable gate arrays (FPGAs) have emerged as a valuable technology in mobile robotics due to their unique ability to be reconfigured to perform specific tasks efficiently. This article presents a comprehensive state-of-the-art review of the implementations of FPGAs in mobile robots. The article explores the various applications where FPGAs have been successfully integrated and discuss their advantages and limitations. The review covers vital areas such as perception, control, navigation, and communication, highlighting each domain's innovative approaches and advancements. Additionally, the study examines FPGAs' impact on mobile robot performance, including improvements in real-time processing, energy efficiency, and adaptability to changing environments. Furthermore, challenges and current efforts in leveraging FPGAs for mobile robotics are discussed, paving the way for exciting developments and possibilities in this rapidly evolving field. This review is a valuable resource for researchers, engineers, and enthusiasts interested in understanding the state of the art and potential of FPGA implementations in mobile robots.

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An Overview of Energies Problems in Robotic Systems

Dec 14, 2023

Journal Energies

publisher MDPI

DOI https://doi.org/10.3390/en16248060

Issue 24

Volume 16

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.

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Quick sequential search algorithm used to decode high-frequency matrices

Aug 19, 2023

Journal International Journal of Electrical and Computer Engineering

publisher World Academy of Science, Engineering and Technology

Issue 8

Volume 17

This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

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Image compression for quality 3D reconstruction

May 1, 2022

Journal Journal of King Saud University-Computer and Information Sciences

publisher Elsevier

DOI https://doi.org/10.1016/j.jksuci.2020.07.012

Issue 5

Volume 34

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.

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Quadtree partitioning scheme of color image based

Jun 18, 2021

Journal Periodicals of Engineering and Natural Sciences

publisher International University of Sarajevo

DOI https://web.archive.org/web/20240604155752/http://dx.doi.org/10.21533/pen.v9i2.2046

Issue 2

Volume 9

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.

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Joint image encryption and compression schemes based on hexa-coding

Apr 1, 2021

Journal Periodicals of Engineering and Natural Sciences

publisher International University of Sarajevo

DOI https://web.archive.org/web/20240418055727/http://dx.doi.org/10.21533/pen.v9i2.1839

Issue 2

Volume 9

This research proposes a new image compression and encryption method depend on a modified JPEG technique combined with the Hexa-Coding algorithm. The compression algorithm starts by dividing an image into 8x8 blocks, then DCT (Discrete Cosine Transform) is applied to all blocks independently followed by uniform quantization. Additionally, the size of blocks is reduced by eliminating insignificant coefficients, and then Arithmetic coding is applied to compress residual coefficients. Finally, Hexa-encoding is applied to the compressed data to further reduce compression size as well as provide encryption. The encryption is accomplished based on five different random keys. The decompression uses a searching method called FMSA (Fast Matching Search Algorithm) which is used for decoding the previously compressed data, followed by Arithmetic decoding) to retrieve residual coefficients. These residuals are padded with zeros to rebuild the original 8x8 blocks. Finally, inverse DCT is applied to reconstruct approximately the original image. The experimental results showed that our proposed image compression and decompression has achieved up to 99% compression ratio while maintaining high visual image quality compared with the JPEG technique.

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Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm

Jul 1, 2020

Journal Array

publisher Elsevier

DOI https://web.archive.org/web/20240418055727/http://dx.doi.org/10.21533/pen.v9i2.1839

Issue 100024

Volume 6

In the present era of the internet and multimedia, image compression techniques are essential to improve image and video performance in terms of storage space, network bandwidth usage, and secure transmission. A number of image compression methods are available with largely differing compression ratios and coding complexity. In this paper we propose a new method for compressing high-resolution images based on the Discrete Fourier Transform (DFT) and Matrix Minimization (MM) algorithm. The method consists of transforming an image by DFT yielding the real and imaginary components. A quantization process is applied to both components independently aiming at increasing the number of high frequency coefficients. The real component matrix is separated into Low Frequency Coefficients (LFC) and High Frequency Coefficients (HFC). Finally, the MM algorithm followed by arithmetic coding is applied to the LFC and HFC matrices. The decompression algorithm decodes the data in reverse order. A sequential search algorithm is used to decode the data from the MM matrix. Thereafter, all decoded LFC and HFC values are combined into one matrix followed by the inverse DFT. Results demonstrate that the proposed method yields high compression ratios over 98% for structured light images with good image reconstruction. Moreover, it is shown that the proposed method compares favorably with the JPEG technique based on compression ratios and image quality.

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Low energy consumption in manet network

May 14, 2020

Journal Periodicals of Engineering and Natural Sciences

publisher International University of Sarajevo

DOI https://web.archive.org/web/20230126220131/http://dx.doi.org/10.21533/pen.v8i2.1336

Issue 2

Volume 8

The aim of this paper is design and develop energy efficient MANET network in wireless networks. One of the most significant and effective protocol based on low energy consumption and number of Ad-hoc is MANET as remote directing convention source nodes forward in network simulator. Less number of nodes in the network would give low energy usage or consumption as the nodes in the network exceeds or increases that will also increase the energy consumption in the network. The designed MANET system is tried with 9, 12, 15 and 18 number of nodes in a system using network simulation-2 (NS-2). Henceforth source node needs to restart over and over which brings about low energy consumption use and use, ectiveness is less and packet space is additionally less and throughput is likewise less and more start to finish delay. Arrangement of this issue in MANET convention which is advanced as the node doesn't advance when demand arrived at their first it checked there is low energy consumption (battery lifetime) and until the node energy consumption is more noteworthy than the limit. Designed MANET examinations of the energy consumption and node energy consumption by maintaining a strategic distance from the low number of nodes in a network. By contrasting energy consumption and node it demonstrates that MANET is far superior to existing framework 802.11 protocol convention based on battery lifetime, energy consumption, throughput, and power transmission. We have performed a comparison between EEM and AODV routing protocol considering different measuring parameters.

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A Low Complexity Slm Scheme for Papr Reduction of OFDM Signals

Sep 1, 0017

Journal Diyala Journal of Engineering Sciences

publisher Diyala University

DOI https://doi.org/10.24237/djes.2017.10306

Issue 3

Volume 10

The selected mapping (SLM) is an effective technique for peak-to-average power reduction (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. SLM has high computational complexity due to the computation of multiple IFFTs. In this paper, low complexity SLM is proposed based on a novel simplified IDFT algorithm developed such that it does not involve any complex arithmetic. The proposed SLM, with U candidate signals, achieves a computational complexity reduction ratio of (1−1/𝑈)%with respect to traditional SLM. This reduction is at the expense of using limited memory and negligible degradation in PAPR reduction performance. The computational core of the proposed SLM is implemented on the Spartan 3E XC3S500E FPGA platform to highlight its hardware implementation issues and to verify its effectiveness.

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FPGA Implementation of Wavelet Filters for DWMT Systems

Mar 28, 0016

Journal Kirkuk Journal of Science

publisher Kirkuk University

DOI https://doi.org/10.32894/kujss.2016.124398

Issue 1

Volume 11

Discrete Wavelet Multi-Tone (DWMT) systems acquired attention due to their high spectral efficiency and high data rates with respect to FFT-based multitone transmission systems. The complexity of the overall system is directly related to that of the elemental building block. In the literature, wavelet filters are designed subject to constraints for minimum interference. The structure of a Minimum Interference Wavelet Filter (MIWF) is very simple even for high filter orders. In this paper, DWMT systems using a two-branch wavelet filter bank in the transmitter and its inverse at the receiver are implemented using the Spartan XC3S1200E FPGA. The details of system implementation are presented for MIWF, Daubechies, and Coiflet wavelet filters. The tests show that, with respect to the other tested systems, the MIWF-based system is simpler, faster and capable to preserve its full precision BER performance even when the filter coefficients word size is reduced to 5 bits.

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