Publicação
Asynchronous encoding scheme for optical camera communication system using two-dimensional transmitter
| Resumo: | This paper presents an innovative approach for optical camera communication (OCC) using two-dimensional matrix LED transmitter where symbols are detected and classified using a lightweight YOLO object detection algorithm. The data-sets built for this study can have any number of symbols (not necessarily a power of two), because we are considering a new differential encoding scheme where data is embedded in symbol transitions. Two different data-sets were produced: one with symbols having a matrix identifier and orientation indicator, and the other lacking these elements. We investigated the performance of YOLOx-S on both data-sets under a variety of conditions, including variable distances, angles, LED matrix brightness, camera exposure time, and lighting environments. The average performance metrics were evaluated for each data-set during training, showing better results with the first data-set. We found that the presence of a matrix identifier significantly improved the detection precision. Furthermore, we examined the effect of LED matrix reflections on object detection accuracy. Overall, this research presents the feasibility of implementing an OCC system with a computer vision-based receiver, establishing a foundation for the development of more complex communication systems. |
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| Autores principais: | Fernandes, Dário |
| Outros Autores: | Matus, Vicente; Figueiredo, Mónica; Alves, Luis Nero |
| Assunto: | Optical camera communication (OCC) Internet of Things You Only Look Once (YOLO) Object detection Visual codes |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade de Aveiro |
| Idioma: | inglês |
| Origem: | RIA - Repositório Institucional da Universidade de Aveiro |
| Resumo: | This paper presents an innovative approach for optical camera communication (OCC) using two-dimensional matrix LED transmitter where symbols are detected and classified using a lightweight YOLO object detection algorithm. The data-sets built for this study can have any number of symbols (not necessarily a power of two), because we are considering a new differential encoding scheme where data is embedded in symbol transitions. Two different data-sets were produced: one with symbols having a matrix identifier and orientation indicator, and the other lacking these elements. We investigated the performance of YOLOx-S on both data-sets under a variety of conditions, including variable distances, angles, LED matrix brightness, camera exposure time, and lighting environments. The average performance metrics were evaluated for each data-set during training, showing better results with the first data-set. We found that the presence of a matrix identifier significantly improved the detection precision. Furthermore, we examined the effect of LED matrix reflections on object detection accuracy. Overall, this research presents the feasibility of implementing an OCC system with a computer vision-based receiver, establishing a foundation for the development of more complex communication systems. |
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