Computer vision project built using Python and OpenCV to accurately detect and count objects in images through effective color segmentation and contour detection techniques.
- Converted images from BGR to HSV color space for robust color detection
- Applied color masking to isolate target objects
- Used Gaussian blur and morphological operations to reduce noise
- Detected contours and filtered them based on area
- Counted and labeled detected objects on the output image
- Python
- OpenCV
- NumPy
- Matplotlib
The system successfully detects and counts objects with high accuracy and visually labels each detected object.