Developed an advanced parking detection system using OpenCV and machine learning.

Responsibilities:

  • Integrated a pre-trained car cascade classifier for vehicle detection.
  • Processed video data and managed video properties like frame width, height, and FPS.
  • Defined and manipulated regions of interest (ROI) in video frames.
  • Applied image processing techniques: grayscale conversion, Gaussian blur, histogram equalization, and morphological operations.
  • Detected parking spots using contour detection and filtered out occupied spots.
  • Calculated real-world distances and angles to parking spots from the camera.
  • Created visual overlays and annotations for detected parking spots and vehicles.
  • Saved processed video with annotated detections.
  • Implemented real-time display and user controls.

Technologies Used:

  • OpenCV, NumPy
  • Video processing (VideoCapture, VideoWriter)
  • Image preprocessing
  • Object detection (cascade classifiers, contour detection)
  • Geometric calculations (distance, angle)
  • Real-time visualization and user interaction

Achievements:

  • Developed a highly accurate parking detection system.
  • Optimized detection algorithm for performance.
  • Created a user-friendly real-time monitoring interface.