Loading...
Please wait, while we are loading the content...
Sistema de detecção em tempo real de faixas de sinalização de trânsito para veículos inteligentes utilizando processamento de imagem
| Content Provider | Semantic Scholar |
|---|---|
| Author | Alves, Thiago |
| Copyright Year | 2017 |
| Abstract | Mobility is an imprint of our civilization. Both freight and passenger transport share a huge infrastructure of connecting links operated with the support of a sophisticated logistic system. As an optimized symbiosis of mechanical and electrical modules, vehicles are evolving continuously with the integration of technological advances and are engineered to offer the best in comfort, safety, speed and economy. Regulations organize the flow of road transportation machines and help on their interactions, stipulating rules to avoid conflicts. But driving can become stressing on different conditions, leaving human drivers prone to misjudgments and creating accident conditions. Efforts to reduce traffic accidents that may cause injuries and even deaths range from re-education campaigns to new technologies. These topics have increasingly attracted the attention of researchers and industries to Image-based Intelligent Transportation Systems that aim to prevent accidents and help your driver in the interpretation of urban signage forms. This work presents a study on real-time detection techniques of traffic signaling signs in urban and intermunicipal environments, aiming at the signaling lanes of the lane for the driver of the vehicle or autonomous vehicle, providing a greater control of the area of traffic destined to the vehicle and to provide alerts of possible risk situations. The main contribution of this work is to optimize how the image processing techniques are used to perform the lanes extraction, in order to reduce the computational cost of the system. To achieve this optimization, small search areas of fixed size and dynamic positioning were defined. These search areas will isolate the regions of the image where the signaling lanes are contained, reducing up to 75% the total area where the techniques used in the extraction of lanes are applied. The experimental results showed that the algorithm is robust in several variations of ambient light, shadows and pavements with different colors, in both urban environments and on highways and motorways. The results show an average detection rate of 98.1%, with average operating time of 13.3 ms. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.lume.ufrgs.br/bitstream/handle/10183/157872/001020894.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
