Vehicle Detection and Recognition for Automated Guided Vehicle

Quoc Bao Truong,Heo Nam Geon,Byung Ryong Lee 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

In this paper, we present a two-stage vision-based approach to detect front and rear vehicle views in road scene images using eigenspace and a support vector machine for classification. The first stage is hypothesis generation (HG), in which potential vehicles are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map to create potential regions where vehicles may be present. The second stage is hypothesis verification (HV). In this stage, all hypotheses are verified by using a Principle Component Analysis (PCA) for feature extraction and a Support Vector Machine (SVM) for classification, which is robust for both front and rear vehicle view detection problems. Our methods have been tested on different real road images and show very good performance.

New Lane Detection Algorithm for Autonomous Vehicles Using Computer Vision

Quoc-Bao Truong,Byung-Ryong Lee 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10

For navigation tasks it is necessary to determine position of the ego vehicle relative to the road. One of the principal approaches is to detect road boundaries and lanes using a vision system in the vehicle. This paper presents a simple and robust method designed to detect and estimate the curvature of road lane boundaries from images provided by a monocular camera. First, we use Vector-lane-concept and Non-uniform B-Spline (NUBS) interpolation method to construct the boundaries road lane. Based on lane detection result, we estimate the curvature of left and right lane boundaries for Autonomous Guided Vehicle systems application. Some experimental results based on real world road images are presented. These simulation results show the efficiency, feasibility and robustness of the algorithm.

Automatic Multi-thresholds Selection for Image Segmentation based on Evolutionary Approach

Quoc Bao Truong,이병룡 제어·로봇·시스템학회 2013 International Journal of Control, Automation, and Vol.11 No.4

Automatic thresholding has been widely used in machine vision for automatic image segmentation. Otsu’s method selects an optimum threshold by maximizing the between-class variance in a grayscale image. However, the method becomes time-consuming when extended to multi-level threshold problems, because excessive iterations are required in order to compute the cumulative probability and the mean of class. In this paper, we focus on the issue of automatic selection for multi-level thresholding, and we greatly improve the efficiency of Otsu’s method for image segmentation based on evolutionary approaches. We have investigated and evaluated the performance of the Otsu and Valley-emphasis thresholding methods. Based on our evaluation results, we have developed many different algorithms for automatic threshold selection based on the evolutionary method using the Modified Adaptive Genetic Algorithm and the Hill Climbing Algorithm. The experimental results show that the evolutionary approach achieves a satisfactory segmentation effect and that the processing time can be greatly reduced when the number of thresholds increases.

Design of a planar, high-gain, substrate-integrated FabryePerot cavity antenna at terahertz frequency

Truong Khang Nguyen,Bao Quoc Ta,박익모 한국물리학회 2015 Current Applied Physics Vol.15 No.9

This paper presents an optimum design of a substrate-integrated cavity-type antenna for use in the terahertz frequency range. The antenna was designed with a frequency-selective surface (FSS) and a planar feeding structure that are both patterned on a high-permittivity gallium-arsenide substrate. The FSS, printed on the bottom side of the substrate, is made of a circular hole array that acts as a partially reflecting mirror. Meanwhile, the planar feeding structure, printed on the top side of the substrate, is a center-fed, open-ended slotline whose ground plane acts as a perfect reflective mirror; thus, it forms a FabryePerot resonator. The optimized antenna produced a maximum boresight gain of 14.3 dBi, a radiation efficiency of 62%, and side-lobe levels of -15.1 dB and -15.0 dB for the E- and H-planes, respectively, at a resonance frequency of 320 GHz. The proposed design exhibits compactness, planarity, and light weight compared with the substrate lens-coupled antenna design.

Deep learning-based functional assessment of piezoelectric-based smart interface under various degradations

Thanh-Truong Nguyen,Jeong-Tae Kim,Quoc-Bao Ta,Duc-Duy Ho,Thi Tuong Vy Phan,Thanh-Canh Huynh 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.1

The piezoelectric-based smart interface technique has shown promising prospects for electro-mechanical impedance (EMI)-based damage detection with various successful applications. During the process of EMI monitoring and damage identification, the operational functionality of the smart interface device is a major concern. In this study, common functional degradations that occurred in the smart interface are diagnosed using a deep learning-based method. Firstly, the effect of functional degradations on the EMI responses is analytically discussed. Secondly, a critical structural joint is selected as the test structure from which EM measurement using the smart interface is conducted. Thirdly, a numerical model corresponding to the experimental model is established and updated to reproduce the measured EMI responses. By using the updated numerical model, the EMI responses of the smart interface under the common functional degradations, such as the shear lag effect, the adhesive debonding, the sensor breakage, and the interface detaching, are simulated; then, the functional degradation-induced EMI changes are characterized. Finally, a convolutional neural network (CNN)-based functional assessment method is newly proposed for the smart interface. The CNN can automatically extract and directly learn optimal features from the raw EMI signals without preprocessing. The CNN is trained and tested using the datasets obtained from the updated numerical model. The obtained results show that the proposed method was successful to classify four types of common defects in the smart interface, even under the effect of noises.

Organic Photocatalysts Based on Dithieno[3,2-b:2',3'-d]pyrrole for Photoinduced Metal-Free Atom Transfer Radical Polymerization

Nhung Thanh Thi Truong,Tam Huu Nguyen,Bao Kim Doan,Le-Thu T. Nguyen,Tam Hoang Luu,Chau Duc Tran,Thiet Quoc Nguyen,Ha Tran Nguyen 한국고분자학회 2021 Macromolecular Research Vol.29 No.11

In this research, three organic photocatalysts, 4-(4H-dithieno[3,2-b:2',3'- d]pyrrol-4-yl)-N,N-diphenylaniline, 4-(pyren-1-yl)-4H-dithieno[3,2-b:2',3'-d]pyrrole and 4-(6b,10-dihydroperylen-3-yl)-4H-dithieno[3,2-b:2',3'-d]pyrrole have been successfully synthesized through C-N coupling reactions. The chemical structures and the optical properties of the obtained organic photocatalysts have been characterized via 1H NMR,13C NMR, elemental analysis, and UV-Vis spectroscopy. Next, these dithieno[3,2-b:2′,3′-d]pyrrole-based photocatalysts have been used for the polymerization of methyl methacrylate, 2-(dimethylamino)ethyl methacrylate and tert-butyl methacrylate monomers under 365 nm UV irradiation, resulting in (meth)acrylate polymers with controlled molecular weights and low polydispersity indexes.

머신비전을 이용한 도로상의 보행자 검출에 관한 연구

이병룡(Byung-Ryong Lee),Quoc Bao Truong,김형석(Hyoung-Seok Kim),배용환(Yong-Hwan Bae) 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.5

In this paper, we present a two-stage vision-based approach to detect multi views of pedestrian in road scene images. The first stage is HG (Hypothesis Generation), in which potential pedestrian are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map, and different colors between road background and pedestrian’s clothes to determine the leg position of pedestrian, then a novel symmetry peaks processing is performed to define how many pedestrians is covered in one potential candidate region. Finally, the real candidate region where pedestrian exists will be constructed. The second stage is HV (Hypothesis Verification). In this stage, all hypotheses are verified by Support Vector Machine for classification, which is robust for multi views of pedestrian detection and recognition problems.

유전자알고리즘을 이용한 영상분할 문턱값의 자동선정에 관한 연구

이병룡(Byung-Ryong Lee),Quoc Bao Truong,Van Huy Pham,김형석(Hyoung-Seok Kim) 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.6

In this paper, we focus on the issue of automatic selection for multi-level threshold, and we greatly improve the efficiency of Otsu’s method for image segmentation based on genetic algorithm. We have investigated and evaluated the performance of the Otsu and Valley-emphasis threshold methods. Based on this observation we propose a method for automatic threshold method that segments an image into more than two regions with high performance and processing in real-time. Our paper introduced new peak detection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill Climbing Algorithm), to find the best threshold automatically, accurately, and quickly. The experimental results show that the proposed evolutionary algorithm achieves a satisfactory segmentation effect and that the processing time can be greatly reduced when the number of thresholds increases.

Application of Fuzzy Moving Sliding Surface Approach for Container Cranes

Quang Hieu Ngo,Ngo Phong Nguyen,Quoc Bao Truong,김경한 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2

In this paper, we consider the fuzzy moving sliding surface anti-sway control problem for container cranes. We first introduce the dynamic model of container cranes. Then, we develop the coupled sliding surface which ensures the asymptotic stability of the closed-loop system. Based on the proposed sliding surface, we propose the continuous sliding mode control law which guarantees the reachability of the sliding variable to zero in finite time. Hence, the proposed controller first guarantees the finite-time convergence to the sliding surface and then achieves the stability of the closed-loop system in the predefined sliding surface. Besides, in order to obtain the effective gains for the proposed sliding variable, the fuzzy logic system is employed. To illustrate the efficiency of the proposed control law, simulation results are provided.