Badania dokładności automatycznych algorytmów wizyjnych klasyfikujących światła sygnalizacji drogowej ; Badania dokładności automatycznych algorytmów wizyjnych klasyfikujących światła sygnalizacji drogowej
Agata ŚWIEREK, Karol PINIARSKI, Kamil KONIAK, Bogusław KOWALSKI ; Agata ŚWIEREK, Karol PINIARSKI, Kamil KONIAK, Bogusław KOWALSKI
This article presents research concerning the recognition of road traffic lights. Initially, vision algorithms were analysed regarding their suitability for implementation in vehicle control systems dedicated to individuals with specific communication needs. The paper presents the results of experimental studies on a vision system for recognising traffic lights, conducted using convolutional neural networks (CNNs). For the experiment, a custom database of traffic light images was prepared. This database was utilised to train a selected Xception CNN model and for processing by a classic algorithm based on colour analysis in the HSV colour space. The obtained classification accuracy results, reaching 98.75%, could serve as a 'green light' for implementing the developed technology to assist driving. The research findings may also find application in driver assistance systems, with particular attention given to the mobility of people with specific needs, such as those with visual impairments.
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This article presents research concerning the recognition of road traffic lights. Initially, vision algorithms were analysed regarding their suitability for implementation in vehicle control systems dedicated to individuals with specific communication needs. The paper presents the results of experimental studies on a vision system for recognising traffic lights, conducted using convolutional neural networks (CNNs). For the experiment, a custom database of traffic light images was prepared. This database was utilised to train a selected Xception CNN model and for processing by a classic algorithm based on colour analysis in the HSV colour space. The obtained classification accuracy results, reaching 98.75%, could serve as a 'green light' for implementing the developed technology to assist driving. The research findings may also find application in driver assistance systems, with particular attention given to the mobility of people with specific needs, such as those with visual impairments.
Warszawa
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Warszawa
Wojskowa Akademia Techniczna ; Wojskowa Akademia Techniczna
oai:ribes-88.man.poznan.pl:2737
doi:10.5604/01.3001.0055.1527 ; doi:10.5604/01.3001.0055.1527
kliknij tutaj, żeby przejść ; kliknij tutaj, żeby przejść
automation and robotics, vision system, convolutional neural network, single-board computer, mobility of people with disabilities ; automation and robotics, vision system, convolutional neural network, single-board computer, mobility of people with disabilities
17 paź 2025
17 paź 2025
0
https://ribes-88.man.poznan.pl/publication/3078
| Nazwa wydania | Data |
|---|---|
| Research on the Accuracy of Automatic Vision Algorithms for Classifying Traffic Lights | 17 paź 2025 |
Góral Piotr Pawłowski Paweł Nowacki Wiktor Wróbel Jakub