NIGHT MODE PROHIBITORY TRAFFIC SIGNS DETECTION

被引:0
|
作者
Biswas, Rubel [1 ]
Khan, Arif [1 ]
Alom, Md. Zahangir [1 ]
Khan, Mumit [1 ]
机构
[1] BRAC Univ, Dept Comp Sci & Engn, Dhaka, Bangladesh
来源
2013 INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV) | 2013年
关键词
Traffic signs; MSRCR; Hough transform; RECOGNITION; RETINEX;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Prohibitory traffic signs play an important role in guiding, warning and regulating traffic system. As driving over the speed limit is often the major cause of accidents, detecting this group of prohibitory signs may reduce this danger. This paper presents an approach to detecting speed limit signs at night mode which is based on Multi-Scale Retinex Color Restoration and Hough Transform. Experiment to check the strength of this approach shows that approximately 96.6% of the prohibitory traffic signs invoked for this test were successfully detected. This test was carried out at dark mode images from different country.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] An application of Faster R-CNN for the detection and recognition of Ecuadorian traffic signs
    Flores-Calero, Marco
    Albuja, Alberto
    Gualsaqui, Marco
    Jose Ayala, Maria
    Gallegos, Joselyn
    2022 IEEE COLOMBIAN CONFERENCE ON COMMUNICATIONS AND COMPUTING, COLCOM, 2022,
  • [32] An Approach towards Service System Building for Road Traffic Signs Detection and Recognition
    Kryvinska, Natalia
    Poniszewska-Maranda, Aneta
    Gregus, Michal
    9TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN-2018) / 8TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2018), 2018, 141 : 64 - 71
  • [33] A practical approach for detection and classification of traffic signs using Convolutional Neural Networks
    Aghdam, Hamed Habibi
    Heravi, Elnaz Jahani
    Puig, Domenec
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2016, 84 : 97 - 112
  • [34] Traffic Signs Detection and Segmentation Based on the Improved Mask R-CNN
    Qian, Huimin
    Ma, Yilong
    Chen, Wei
    Li, Tao
    Zhuo, Yi
    Xiang, Wenbo
    2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC), 2021, : 8241 - 8246
  • [35] Mental representation of traffic signs and their classification: Warning signs
    Luis Vilchez, Jose
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2019, 64 : 447 - 462
  • [36] Mental representation of traffic signs and their classification: informative signs
    Luis Vilchez, Jose
    THEORETICAL ISSUES IN ERGONOMICS SCIENCE, 2021, 22 (04) : 441 - 456
  • [37] Traffic Signs Recognition Based on PCA-SIFT
    Gao Hongwei
    Liu Chuanyin
    Yu Yang
    Li Bin
    2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2014, : 5070 - 5075
  • [38] A Real-Time Detection of Indian Traffic Signs for Visually Impaired People
    Madake, Jyoti
    Badade, Mahesh
    Barve, Mrunal
    Bhatlawande, Shripad
    Shilaskar, Swati
    INTELLIGENT SYSTEMS AND APPLICATIONS, ICISA 2022, 2023, 959 : 237 - 247
  • [39] Occluded Traffic Signs Recognition
    Yen, Shwu-Huey
    Shu, Chun-Yung
    Hsu, Hui-Huang
    ADVANCES IN INFORMATION AND COMMUNICATION, VOL 2, 2020, 1130 : 794 - 804
  • [40] Object Detection-Based System for Traffic Signs on Drone-Captured Images
    Naranjo, Manuel
    Fuentes, Diego
    Muelas, Elena
    Diez, Enrique
    Ciruelo, Luis
    Alonso, Cesar
    Abenza, Eduardo
    Gomez-Espinosa, Roberto
    Luengo, Inmaculada
    DRONES, 2023, 7 (02)