A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication
In a vehicular optical camera communication (VOCC) system, digital information is transmitted using LED panels and received using cameras. The transmitted bits are obtained by processing the captured images to detect the ON and OFF statuses of LEDs in the array. In determining the LED status, the cu...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8761946/ |
| _version_ | 1818948435912425472 |
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| author | Trong-Hop Do Myungsik Yoo |
| author_facet | Trong-Hop Do Myungsik Yoo |
| author_sort | Trong-Hop Do |
| collection | DOAJ |
| description | In a vehicular optical camera communication (VOCC) system, digital information is transmitted using LED panels and received using cameras. The transmitted bits are obtained by processing the captured images to detect the ON and OFF statuses of LEDs in the array. In determining the LED status, the current LED bit detection algorithms only rely on the grayscale, which is an unreliable feature of LEDs. Consequently, they exhibit poor performance in unfavorable conditions. The contribution of this paper is the proposed multi-feature LED bit detection algorithm that employs three new features of LED: average greyscale ratio (AGR), gradient radial inwardness (GRI), and neighbor greyscale ratio (NGR). Two features, AGR and GRI, individually have substantially more discriminability of LED statuses than greyscale. More importantly, the three proposed features differentiate LED statuses under different perspectives. Consequently, the combination of the three features using Fisher linear discriminant analysis (FLDA) yields outstanding accuracy and robustness of bit detection, even in severe conditions. Highly realistic simulations of a VOCC system are conducted to verify the superiority and robustness of the proposed algorithm. |
| first_indexed | 2024-12-20T08:46:46Z |
| format | Article |
| id | doaj.art-8947fc452cfe41659e4cf5da91bbd55f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T08:46:46Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8947fc452cfe41659e4cf5da91bbd55f2022-12-21T19:46:13ZengIEEEIEEE Access2169-35362019-01-017957979581110.1109/ACCESS.2019.29286008761946A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera CommunicationTrong-Hop Do0Myungsik Yoo1https://orcid.org/0000-0002-5578-6931School of Electronic Engineering, Soongsil University, Seoul, South KoreaSchool of Electronic Engineering, Soongsil University, Seoul, South KoreaIn a vehicular optical camera communication (VOCC) system, digital information is transmitted using LED panels and received using cameras. The transmitted bits are obtained by processing the captured images to detect the ON and OFF statuses of LEDs in the array. In determining the LED status, the current LED bit detection algorithms only rely on the grayscale, which is an unreliable feature of LEDs. Consequently, they exhibit poor performance in unfavorable conditions. The contribution of this paper is the proposed multi-feature LED bit detection algorithm that employs three new features of LED: average greyscale ratio (AGR), gradient radial inwardness (GRI), and neighbor greyscale ratio (NGR). Two features, AGR and GRI, individually have substantially more discriminability of LED statuses than greyscale. More importantly, the three proposed features differentiate LED statuses under different perspectives. Consequently, the combination of the three features using Fisher linear discriminant analysis (FLDA) yields outstanding accuracy and robustness of bit detection, even in severe conditions. Highly realistic simulations of a VOCC system are conducted to verify the superiority and robustness of the proposed algorithm.https://ieeexplore.ieee.org/document/8761946/Visible light communicationoptical camera communicationvehicleLEDdetection |
| spellingShingle | Trong-Hop Do Myungsik Yoo A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication IEEE Access Visible light communication optical camera communication vehicle LED detection |
| title | A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication |
| title_full | A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication |
| title_fullStr | A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication |
| title_full_unstemmed | A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication |
| title_short | A Multi-Feature LED Bit Detection Algorithm in Vehicular Optical Camera Communication |
| title_sort | multi feature led bit detection algorithm in vehicular optical camera communication |
| topic | Visible light communication optical camera communication vehicle LED detection |
| url | https://ieeexplore.ieee.org/document/8761946/ |
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