A Real-Time Speed Limit Sign Recognition System for Autonomous Vehicle Using SSD Algorithm

被引:0
|
作者
Abu Mangshor, Nur Nabilah [1 ]
Saharuddin, Nor Syahirah [1 ]
Ibrahim, Shafaf [1 ]
Fadzil, Ahmad Firdaus Ahmad [1 ]
Abu Samah, Khyrina Airin Fariza [1 ]
机构
[1] UiTM Cawangan Melaka, Fac Comp & Math Sci, Kampus Jasin, Merlimau, Melaka, Malaysia
关键词
Traffic Sign Recognition; TSR; Speed Limit Sign; Autonomous Vehicle; AV; Single Shot Multi-Detector; SSD; CLASSIFICATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In today's technology-driven world, there are a lot of devices and products have been invented including the Autonomous Vehicle (AV). Autonomous vehicle is a driverless vehicle which able to drive on its own. It works with the aid of various embedded systems and sensors that help the AV to function greatly. Speed limit signs recognition is one of the TSR essential features for AV where it helps to automatically detect and recognize speed limit signs on the road. There are many speed limit signs available on the road including 30km/h, 60km/h, 90km/h signs and to name a few. However, the inter-class similarity among these speed limit signs has created a challenge for the TSR system in detection and recognition process. Therefore, this study proposes image processing technique to develop the speed limit sign recognition for TSR system utilizing a single layer network called Single Shot Multibox Detector (SSD) algorithm. The German Traffic Sign Dataset (GTSD) is used for the purpose of training the model and the model is then tested using the real-time images of standard Malaysian speed limit signs. An accuracy testing using confusion matrix is conducted to find the overall accuracy of the system. A total 100 images are used during testing and the system achieved over 92.4% of the average accuracy for detection and recognition of the speed limit signs.
引用
收藏
页码:126 / 130
页数:5
相关论文
共 50 条
  • [41] Real-Time Traffic Sign Detection and Recognition using CNN
    Santos, D.
    Silva, F.
    Pereira, D.
    Almeida, L.
    Artero, A.
    Piteri, M.
    de Albuquerque, V
    [J]. IEEE LATIN AMERICA TRANSACTIONS, 2020, 18 (03) : 522 - 529
  • [42] Real-time Sign Language Recognition using Computer Vision
    Raval, Jinalee Jayeshkumar
    Gajjar, Ruchi
    [J]. ICSPC'21: 2021 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION (ICPSC), 2021, : 542 - 546
  • [43] Real-Time American Sign Language Recognition System by Using Surface EMG Signal
    Savur, Celal
    Sahin, Ferat
    [J]. 2015 IEEE 14TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA), 2015, : 497 - 502
  • [44] Real-time recognition of road traffic sign in moving scene image using genetic algorithm
    Han, L
    Ding, L
    Qi, L
    [J]. PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4, 2002, : 1027 - 1030
  • [45] Real-Time Vehicle Navigation using Modified A* Algorithm
    Nayak, Snehal
    Narvekar, Meera
    [J]. 2017 INTERNATIONAL CONFERENCE ON EMERGING TRENDS & INNOVATION IN ICT (ICEI), 2017, : 116 - 122
  • [46] Real-time recognition of corridor under varying lighting conditions for autonomous vehicle
    Minami, M
    Agbanhan, J
    Suzuki, H
    Asakura, T
    [J]. PROCEEDINGS OF THE IEEE INTELLIGENT VEHICLES SYMPOSIUM 2000, 2000, : 320 - 325
  • [47] Traffic Sign Recognition System for Autonomous Vehicle Using Cascade SVM Classifier
    Wahyono
    Kurnianggoro, Laksono
    Hariyono, Joko
    Jo, Kang-Hyun
    [J]. IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2014, : 4081 - 4086
  • [48] A Real-Time American Sign Language Recognition System using Convolutional Neural Network for Real Datasets
    Kadhim, Rasha Amer
    Khamees, Muntadher
    [J]. TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS, 2020, 9 (03): : 937 - 943
  • [49] A study on data parallel optimization for real-time vehicle recognition algorithm
    Yang, Chunyang
    Wen, Xuezhi
    Yuan, Huai
    Duan, Bobo
    [J]. 2007 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE, VOLS 1 AND 2, 2007, : 880 - +
  • [50] Speed limit sign detection and recognition system using SVM and MNIST datasets
    Saadna, Yassmina
    Behloul, Ali
    Mezzoudj, Saliha
    [J]. NEURAL COMPUTING & APPLICATIONS, 2019, 31 (09): : 5005 - 5015