Real-time traffic sign detection and recognition

Herbschleb, Ernst

doi:10.1117/12.806171

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Literature [ 15 ] designed YUV space and his space conversion algorithms, which greatly improved the speed and accuracy of real-time video image processing. In addition, lab [ 16 ], YCB cr [ 17 ], and LUV [ 18 ] spaces can be used for conversion, but they are not widely used in general.…”

Section: Related Workmentioning

confidence: 99%

Yolo-Based Traffic Sign Recognition Algorithm

Zhang

Li³

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

With the rapid development of intelligent transportation, more and more vehicles are equipped with intelligent traffic sign recognition systems, which can reduce the potential safety hazards caused by human cognitive errors. Therefore, a more safe and reliable traffic sign recognition system is the demand of drivers, and it is also the research hotspot of current automobile manufacturers. However, the pictures taken by the actual driving car are inevitably distorted and blurred. In addition, there are external uncontrollable factors, such as the impact of bad weather, which make the research of traffic sign recognition system face many difficulties, and the practical application is far from mature. In order to solve the above challenges, this paper proposes a Yolo model for traffic sign recognition. Firstly, the traffic signs are roughly divided into several categories and then preprocessed according to the characteristics of various types of signs. The processed pictures are input into the optimized convolutional neural network to subdivide the categories to obtain the specific categories. Finally, the proposed recognition algorithm is tested with the data set based on the German traffic sign recognition standard and compared with other baseline algorithms. The results show that the algorithm greatly improves the running speed on the basis of ensuring a high classification accuracy and is more suitable for traffic sign recognition system.

show abstract

Section: Related Workmentioning

confidence: 99%

Yolo-Based Traffic Sign Recognition Algorithm

Zhang

Li³

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Road sign inventory and road mark extraction are asset management applications with a great potential for automation (Herbschleb & de With, 2009). The integrated use of aerial and terrestrial images is expected to improve the efficiency, especially when the registration of the two types of imagery is of high fidelity (Tournaire et al, 2006).…”

Section: Image Content Analysismentioning

confidence: 99%

Core Spatial Data

2009

Publications on Geodesy - Green Series

View full text Add to dashboard Cite

Two domain models for topography have been independently established in the Netherlands: Information Model Geography (for large scale topography) and TOP10NL (for small scale topography). The two domain models IMGeo and TOP10NL model the content and meaning of existing datasets which will be legally established as key registers for the national Spatial Data Infrastructure (SDI). Since both domain models and corresponding datasets represent the same types of object and cover the same geographical extent, the question is if one domain model and one register topography will be feasible to serve the notion of 'collect once, use many times' within the Dutch SDI. This paper contains a thorough comparison of how similar concepts in the two domain models are defined. The conclusion is that two key registers topography need to be kept for the moment. The main reason is the differences in content due to differences in data source, providers, objectives and stake holders. However since many differences seem random and easy to solve, harmonising of concepts is recommended before integrating the models. For the integration the paper proposes a Base Model Topography that models how TOP10NL data can be derived from IMGeo data to serve the goal: collect data once, maintain it at two key registers to use it many times.

show abstract

Real-time traffic sign detection and recognition

Cited by 2 publications

References 0 publications

Yolo-Based Traffic Sign Recognition Algorithm

Yolo-Based Traffic Sign Recognition Algorithm

Core Spatial Data

Contact Info

Product

Resources

About