Computer Vision-Based Harmonic Oscillation Analysis

This project is a powerful tool designed to analyze the harmonic oscillation of objects using computer vision techniques. Leveraging a variety of libraries, including OpenCV for video feed processing, SciPy for data analysis, NumPy for numerical operations, and PyQt5 for a user-friendly graphical interface, it offers a wide range of features to facilitate detailed analysis.

github repo: https://github.com/rudrodip/Harmonic-Oscillator-CV

blog: https://rudrodip.vercel.app/blog/harmonic-oscillation-analyzer

Key Features

1. Bob Color Detection: The system can accurately detect the bob of any color, providing flexibility in object selection.

2. Contour Detection Options: Choose from three contour detection methods - color-based, edge-based, or circle detection - to suit your specific tracking needs.

3. Video Source Flexibility: Analyze harmonic oscillations from various sources, including:

   • Local Video: Process videos stored on your device for in-depth analysis.

   • Webcam: Utilize your webcam for real-time tracking and motion analysis.

4. Display Options:

   • Main Video: Observe the original video feed.

   • Contours: Visualize the detected contours for better tracking insights.

   • Mask: Monitor the real-time masking process and make adjustments as needed.

5. Real-time Parameter Adjustment: Easily fine-tune masking parameters in real time and save your configurations for future reference.

6. Parameter Saving: After prediction, you can conveniently save the calculated parameters for further analysis and documentation.

7. Frame Offset Control: Within the code, set a frame offset and utilize a built-in function to save critical data points, streamlining the analysis process.

8. Rotation Compensation: The system intelligently compensates for video rotation, ensuring accurate analysis even when dealing with rotated footage.

9. Prediction Capabilities:

   • Pivot Point Prediction: Accurately predict the pivot point of the bob's motion.

   • Mean Point Determination: Find the mean point of the bob's trajectory.

   • Path Analysis: Analyze the bob's path and generate predictions of its corresponding harmonic motion equation.

10. Physical Properties Estimation: Utilizing parameters derived from the predicted harmonic motion equation, the system can estimate crucial physical properties of the system, such as the length of the string or other relevant characteristics.

This project provides a robust and versatile platform for in-depth analysis of harmonic oscillations using computer vision techniques. Its user-friendly interface, real-time adjustments, and predictive capabilities make it an invaluable tool for researchers, educators, and enthusiasts exploring dynamic systems and motion analysis.