研究目的
To develop a technique for live shadow detection in video frames of solar panels using the Otsu thresholding algorithm, enabling automatic detection of shaded frames and adjustment of drone camera position to avoid shadows for accurate monitoring.
研究成果
The Otsu thresholding method effectively detects shadows in solar panel frames, allowing for automatic adjustment of drone camera positions to avoid shadow interference. This enhances the accuracy of solar plant monitoring. Future research will focus on using shadow position to locate light sources and further optimize camera angles.
研究不足
The method may be sensitive to noise and variations in illumination, and it relies on pixel-level processing which could lead to unsatisfactory performance in complex real-world images. Future work is needed to improve accuracy and handle diverse environmental conditions.
1：Experimental Design and Method Selection:
The experiment uses the Otsu thresholding algorithm for image segmentation to detect shadows in video frames. The method involves processing frames to identify shadowed areas based on intensity differences.
2：Sample Selection and Data Sources:
Frames are captured from a video of a solar panel installation at Abdelmalek Essaadi University, Faculty of Sciences, Energetic Department.
3：List of Experimental Equipment and Materials:
Drones equipped with cameras for video capture, solar panels for monitoring, and computational tools for implementing the Otsu algorithm.
4：Experimental Procedures and Operational Workflow:
Capture video frames of solar panels, apply Otsu thresholding to each frame to detect shadows, and use the results to adjust the drone's camera position to avoid shadows in subsequent captures.
5：Data Analysis Methods:
The Otsu algorithm is used to compute thresholds for shadow detection, with results visualized to confirm shadow presence.
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