Browsing by Author "Abdulrahim K."
Now showing 1 - 9 of 9
Results Per Page
Sort Options
- Some of the metrics are blocked by yourconsent settings
Publication Dynamic features descriptor for road user recognition using hierarchal graph dynamic gradient pattern(Blue Eyes Intelligence Engineering and Sciences Publication, 2019) ;Al-Smadi M. ;Abdulrahim K. ;Salama R.A. ;Faculty of Engineering and Built Environment ;Faculty of Science and TechnologyUniversiti Sains Islam Malaysia (USIM)Accurate and precise vehicle recognition and classification play a major role in analyzing and understanding traffic surveillance systems. This paper proposes a dynamic feature descriptor to recognize and classify road users based on graph representation. Local gradient patterns are computed based on the grayscale difference on the four directions across the center pixels. Dynamic gradients are determined according to the effective gradient computed as the mean value of all gradients. Hierarchal Graph using angular rotation pattern are applied to extract Dynamic Gradient Patterns (DGP). The central pixel is represented by Hierarchal Graph of Dynamic Gradient Patterns (HG-DGP).The proposed method learns dynamic representation adaptively to achieve efficient recognition with higher accuracy and lower pre-processing. The experimental results show that the proposed technique combined with support vector machine is efficient and discriminative for road user recognition and classification. � BEIESP. - Some of the metrics are blocked by yourconsent settings
Publication Finite-Horizon LQR Control of Quadrotors on SE2(3)(Institute of Electrical and Electronics Engineers Inc., 2020) ;Cohen M.R. ;Abdulrahim K.Forbes J.R.This letter considers optimal control of a quadrotor unmanned aerial vehicles (UAV) using the discrete-time, finite-horizon, linear quadratic regulator (LQR). The state of a quadrotor UAV is represented as an element of the matrix Lie group of double direct isometries, SE2(3). The nonlinear system is linearized using a left-invariant error about a reference trajectory, leading to an optimal gain sequence that can be calculated offline. The reference trajectory is calculated using the differentially flat properties of the quadrotor. Monte-Carlo simulations demonstrate robustness of the proposed control scheme to parametric uncertainty, state-estimation error, and initial error. Additionally, when compared to an LQR controller that uses a conventional error definition, the proposed controller demonstrates better performance when initial errors are large. � 2016 IEEE. - Some of the metrics are blocked by yourconsent settings
Publication Increased error observability of an inertial Pedestrian navigation system by rotating IMU(Institute for Research and Community Services, Institut Teknologi Bandung, 2014) ;Abdulrahim K. ;Hide C. ;Moore T. ;Hill C. ;Universiti Sains Islam Malaysia (USIM)University of NottinghamIndoor pedestrian navigation suffers from the unavailability of useful GNSS signals for navigation. Often a low-cost non-GNSS inertial sensor is used to navigate indoors. However, using only a low-cost inertial sensor for the system degrades its performance due to the low observability of errors affecting such low-cost sensors. Of particular concern is the heading drift error, caused primarily by the unobservability of z-axis gyro bias errors, which results in a huge positioning error when navigating for more than a few seconds. In this paper, the observability of this error is increased by proposing a method of rotating the inertial sensor on its y-axis. The results from a field trial for the proposed innovative method are presented. The method was performed by rotating the sensor mechanically-mounted on a shoe-on a single axis. The method was shown to increase the observability of z-axis gyro bias errors of a low-cost sensor. This is very significant because no other integrated measurements from other sensors are required to increase error observability. This should potentially be very useful for autonomous low-cost inertial pedestrian navigation systems that require a long period of navigation time. � 2014 Published by ITB Journal Publisher. - Some of the metrics are blocked by yourconsent settings
Publication Investigating the use of rotating foot mounted inertial sensors for positioning(2012) ;Hide C. ;Moore T. ;Hill C. ;Abdulrahim K. ;University of NottinghamUniversiti Sains Islam Malaysia (USIM)Foot mounted inertial sensors have been used in recent literature to provide high accuracy positioning through the use of zero velocity updates (ZUPT) every time the user takes a step. When only ZUPTs are used, the remaining positioning errors are primarily a result of heading drift due to poor observability. This paper demonstrates that a single axis rotation of an Inertial Measurement Unit (IMU) provides improved observability of IMU accelerometer and gyro biases. In particular, all gyro biases become observable when the IMU is rotated about a single horizontal axis. This results in a significant reduction of heading errors and hence also improves positioning accuracy. This paper first presents results using simulated data from a static environment to verify observability of bias states. The paper then describes the results from a physical implementation of a rotating IMU platform that is attached to a user's shoe. It is demonstrated that maximum position errors are significantly reduced to less than 1.3m over three trials for the rotating IMU compared to 12.4m for the non-rotating IMU. - Some of the metrics are blocked by yourconsent settings
Publication A new spatio-temporal background–foreground bimodal for motion segmentation and detection in urban traffic scenes(Springer London, 2019) ;Al-Smadi M. ;Abdulrahim K. ;Seman K. ;Salam R.A. ;Faculty of Engineering and Built Environment ;Faculty of Science and TechnologyUniversiti Sains Islam Malaysia (USIM)Automatic vehicle detection in urban traffic surveillance is an important and urgent issue, since it provides necessaryinformation for further processing. Conventional techniques utilize either motion segmentation or appearance-baseddetection, which involves either poor adaptation or high computation. The complexity of urban traffic scenarios lies in slowmotion temporarily stopped or parked vehicles, dynamic background, and sudden illumination variations. In this paper, anew motion segmentation technique is proposed based on spatio-temporal background–foreground bimodal. The temporalbackground information is modeled using a weighted sigma–delta estimation, cumulative frame differencing is used tomodel the foreground pixels, and the spatial correlation between neighboring pixels is utilized to combine both backgroundand foreground models. The median of consecutive frame difference adapts sudden illumination variation, update back-ground model, and reinitialize foreground model. Comparative experimental results for typical urban traffic sequencesshow that the proposed technique achieves robust and accurate segmentation, which improves adaptation, reduce falsedetection, and satisfy real-time requirements. KeywordsMotion segmentation-Background subtraction-Cumulative frame differencing-Sigma–delta filter-Vehicle detection - Some of the metrics are blocked by yourconsent settings
Publication Packet loss rate differentiation in slotted Optical packet switching OCDM/WDM(Universitas Ahmad Dahlan, 2017) ;Najah O. ;Seman K. ;Abdulrahim K. ;Faculty of Science and TechnologyUniversiti Sains Islam Malaysia (USIM)We propose a multi-class mechanism for Optical Code Division Multiplexing (OCDM), Wavelength Division Multiplexing (WDM) Optical Packet Switch (OPS) architecture capable of supporting Quality of Service (QoS) transmission. OCDM/WDM has been proposed as a competitive hybrid switching technology to support the next generation optical Internet. This paper addresses performance issues in the slotted OPS networks and proposed four differentiation schemes to support Quality of Service. In addition, we present a comparison between the proposed schemes as well as, a simulation scheduler design which can be suitable for the core switch node in OPS networks. Using software simulations the performance of our algorithm in terms of losing probability, the packet delay, and scalability is evaluated. � 2017 Universitas Ahmad Dahlan. - Some of the metrics are blocked by yourconsent settings
Publication Real-time framework for image dehazing based on linear transmission and constant-time airlight estimation(Elsevier Inc., 2018) ;Alajarmeh A. ;Salam R.A. ;Abdulrahim K. ;Marhusin M.F. ;Zaidan A.A. ;Zaidan B.B. ;Faculty of Science and Technology ;Universiti Sains Islam Malaysia (USIM)Universiti Pendidikan Sultan Idris (UPSI)The haze phenomenon exerts a degrading effect that decreases contrast and causes colour shifts in outdoor images. The presence of haze in digital images is bothersome, unpleasant, and, occasionally, even dangerous. The atmospheric light scattering (ALS) model is widely used to restore hazy images. In this model, two unknown parameters should be estimated: airlight and scene transmission. The quality of dehazed images depends considerably on the accuracy of both estimates. Classic methods typically determine airlight based on the brightest pixels in an image. However, in the traffic scene context, this estimate is compromised when other light sources, such as vehicle headlights from the opposite direction, are present. Transmission estimation is usually more complicated. Hence, the complexity of the overall dehazing process is dependent on this estimate. To address this issue, this study proposes a framework for constant-time airlight and linear transmission estimation. This framework consists of two methods: airlight by image integrals (ALII), which is utilized to estimate the airlight value in real time with high accuracy, and bounded transmission (BT), which is proposed for the linear and simplified estimation of transmission maps. To evaluate the proposed framework, three image datasets are used: (1) seven images that are gathered from the works of existing methods (called the global dataset); (2) the synthetic foggy road image database (FRIDA), which is a synthetically generated dataset for simulating different bad weather conditions; and (3) a dataset of images that were extracted from videos in Malaysia (IV-M), which consists of images that were extracted from traffic video sequences, which were captured in various weather conditions from 2014 to 2016 in Malaysia. Experimental results show that the proposed framework is at least seven times faster than existing methods. In addition, the ANOVA test proves that the quality of the dehazed images is statistically similar to or better than the image quality that was achieved using existing methods. � 2018 Elsevier Inc. - Some of the metrics are blocked by yourconsent settings
Publication Rotating a mems inertial measurement unit for a foot-mounted pedestrian navigation(Science Publications, 2014) ;Abdulrahim K. ;Hide C. ;Moore T. ;Hill C. ;Faculty of Science and Technology ;Universiti Sains Islam Malaysia (USIM)University of NottinghamPedestrian navigation especially indoors suffers from the unavailability of useful GNSS signals for positioning. Alternatively, a low-cost Inertial Measurement Unit (IMU) positioning system that does not depend on the GNSS signal can be used for indoor navigation. However its performance is still compromised because of the fastaccumulating heading drift error affecting such a low-cost IMU sensor. This results in a huge positioning error when navigating more than a few seconds using only the low-cost sensor. In this study, real field trials results are presented when a foot-mounted IMU is rotated on a single axis. Two promising results have been obtained. First, it mitigates the heading drift error significantly and second, it increases the observability of IMU z-axis gyro bias error. This has resulted in a greatly reduced error in position for the low-cost pedestrian navigation system. � 2014 K. Abdulrahim et al. - Some of the metrics are blocked by yourconsent settings
Publication Traffic surveillance: A review of vision based vehicle detection, recognition and tracking(Research India Publications, 2016) ;Al-Smadi M. ;Abdulrahim K. ;Salam R.A. ;Islamic Science InstituteUniversiti Sains Islam Malaysia (USIM)Video-based analysis of traffic surveillance is an active area of research, which has a wide variety of applications in intelligent transport systems (ITSs). In particular, urban environments are more challenging than highways due to camera placement, background clutter, and vehicle pose or orientation variations. This paper provide a comprehensive review of the state-of-the-art video processing techniques for vehicle detection, recognition and tracking with analytical description. In this survey, we categorize vehicle detection into motion and appearance based techniques, varying from simple frame differencing and adaptive median filtering, to more sophisticated probabilistic modeling and feature extracting. We also discuss vehicle recognition and classification utilizing vehicle attributes like color, license plate, logo and type, provide a detailed description of the advances in the field. Next we categorize tracking into model, region and features based tracing. Finally tracking algorithms including Kalman and particle filter are discussed in term of correspondence matching, filtering, estimation and dynamical models. � Research India Publications.