Automatic Detection and Recognition of Traffic Signs using Geometric Structure Analysis

2006 ◽  
Author(s):  
Vavilin Andrey ◽  
Kang Hyun Jo
Keyword(s):  
Structure Analysis ◽  
Geometric Structure ◽  
Automatic Detection ◽  
Traffic Signs ◽  
Detection And Recognition

Automatic Detection and Recognition of Text-Based Traffic Signs from images

2018 ◽  
Vol 16 (12) ◽  
pp. 2947-2953
Author(s):  
Gustavo Henrique de Oliveira ◽  
Francisco Assis da Silva ◽  
Danillo Roberto Pereira ◽  
Leandro Luiz de Almeida ◽  
Almir Olivette Artero ◽  
...  
Keyword(s):  
Automatic Detection ◽  
Traffic Signs ◽  
Detection And Recognition

Automatic detection and recognition of traffic signs

2010 ◽  
Author(s):  
M. Sajjad Hossain ◽  
M. Mahmudul Hasan ◽  
M. Ameer Ali ◽  
Md. Humayun Kabir ◽  
A B M Shawkat Ali
Keyword(s):  
Automatic Detection ◽  
Traffic Signs ◽  
Detection And Recognition

scholarly journals Hybrid Framework on Automatic Detection and Recognition of Traffic Display board Signs

2021 ◽  
Vol 3 (3) ◽  
pp. 191-205
Author(s):  
R Kanthavel
Keyword(s):  
Traffic Accidents ◽  
High Efficiency ◽  
Automatic Detection ◽  
Academic Community ◽  
Traffic Signs ◽  
Identification Rate ◽  
Detection And Identification ◽  
Autonomous Cars ◽  
Good Identification ◽  
Detection And Recognition

Automatically identifying traffic signs is a challenging and time-consuming process. As the academic community pays more attention to traditional algorithms for vision-based detection, tracking, and classification, three main criteria drive the investigation, they are detection, tracking, and classification. It is capable of performing detection and identification operations to minimize traffic accidents and move towards autonomous cars. A novel method proposed in this paper is based on moment invariants and neural networks for performing detection and recognition with classification, and it also includes automatic detection and identification of traffic signs and traffic board text that uses colour segmentation. Aside from the proposed structure, it is also required to identify the potential graphic road marking with text. This research article contains two algorithms, which are used to accurately classify the board text. The detection through image segmentation and recognition can be done by using the CNN algorithm. Finally, the classification is performed by the SVM framework. Therefore, the proposed framework will be very accurate and reliable with high efficiency, which has been proven in many big dataset applications. The proposed algorithm is tested with various datasets and provided good identification rate compared to the traditional algorithm.

Detection and recognition of text traffic signs above the road

2021 ◽  
Vol 35 (2) ◽  
pp. 69
Author(s):  
Wei Sun ◽  
Yangtao Du ◽  
Xu Zhang ◽  
Guoce Zhang
Keyword(s):  
Traffic Signs ◽  
The Road ◽  
Detection And Recognition

Automatic Detection and Recognition of Object to Help Visually Impaired People while Visiting Liberation War Museum in Bangladesh

2021 ◽  
Author(s):  
Md. Mehedi Hasan ◽  
Khairul Alam ◽  
Md. Rejaul Alam ◽  
Md. Nahiduzzaman Sajeeb ◽  
Afsana Akther Ankhi ◽  
...  
Keyword(s):  
Visually Impaired ◽  
Automatic Detection ◽  
Visually Impaired People ◽  
Impaired People ◽  
Detection And Recognition

scholarly journals Automatic detection and recognition of silicosis in chest radiograph

2014 ◽  
Vol 24 (6) ◽  
pp. 3389-3395
Author(s):  
Lei Zhu ◽  
Ran Zheng ◽  
Hai Jin ◽  
Qin Zhang ◽  
Wei Zhang
Keyword(s):  
Chest Radiograph ◽  
Automatic Detection ◽  
Detection And Recognition

Detection and recognition of text traffic signs above the road

2021 ◽  
Vol 35 (2) ◽  
pp. 69
Author(s):  
Yangtao Du ◽  
Xu Zhang ◽  
Guoce Zhang ◽  
Wei Sun
Keyword(s):  
Traffic Signs ◽  
The Road ◽  
Detection And Recognition
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