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- W4386211410 abstract "The shadow detection and removal of moving vehicles is a difficult task for the applications of computer vision i.e., vehicle detection, vehicle tracking, vehicle classification, vehicle counting, etc. because the motion of moving vehicles and their cast shadow is the same. Many researchers have published their work on shadow detection of moving vehicles on standard datasets or on the morning/afternoon duration dataset but less research published on shadow detection in low illumination and it is a very tricky task for various applications of computer vision. In this paper, the intensity ratio-based shadow detection method has been proposed along with negative transformation, a gamma correction image preprocessing technique on a self-generated dataset at the Vadodara-Mumbai highway in the evening time. The proposed method has been implemented on 500+ images of a self-generated dataset and the outcomes have been evaluated by shadow detection analysis matrices i.e., shadow detection rate, specificity (true negative rate), precision, F-measure, etc. in reference to ground truth which is obtained using ImageJ software. The average shadow detection rate is 80.18% and the average specificity is 93.96%. The proposed method is simple and robust against the shadow detection of moving vehicles in low illumination." @default.
- W4386211410 created "2023-08-29" @default.
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- W4386211410 date "2023-07-03" @default.
- W4386211410 modified "2023-10-17" @default.
- W4386211410 title "High Accurate Cast Shadow Detection of Moving Vehicles in Low Illumination Environment" @default.
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- W4386211410 doi "https://doi.org/10.1109/piers59004.2023.10221444" @default.
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