This repository hosts my initial project with OpenCV, an open-source computer vision and machine learning software library. The core functionality of this project is to implement a tracker bar for dynamic threshold adjustments in real-time image processing. Currently in development, the project aims to address challenges such as varying light conditions, which can affect the accuracy and stability of threshold-based operations.

• Dynamic Threshold Adjustment: Incorporates a tracker bar allowing users to adjust threshold values interactively to fine-tune image processing results.
• Real-Time Processing: Utilizes a live video feed to apply threshold adjustments and observe changes in real-time.
• Lighting Condition Challenges: Actively being refined to better handle and adapt to changes in lighting conditions, which currently present a challenge to consistent image processing.

• Python: The project is developed in Python, leveraging its simplicity and powerful libraries in computer vision.
• OpenCV (Open Source Computer Vision Library): Used for real-time computer vision operations, particularly in tracking and threshold adjustments.
• Background Subtraction: Employing OpenCV's background subtraction methods for isolating moving objects in the video feed.