💧 Image-Based Water Turbidity Analysis System

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📸 Sample GUI & Output

User Interface

Analysis Results

Feature	Visualization
Original Sample
Red Channel Histogram
Edge Analysis

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🧠 Core Features

• Intuitive GUI: Built with Tkinter for easy image uploading and real-time feedback.
• Automated Preprocessing: Includes watermark removal, noise reduction (Median Filter), and smoothing (Gaussian Blur).
• Advanced Metrics:
  • Average Intensity & Variance
  • Turbidity Index
  • Edge Density (Canny)
  • Particle Count & Density
  • Particle Uniformity
• Visual Analytics: Generates red channel histograms and edge maps.
• Professional Reporting: Automatically exports results into a detailed PDF report with color-coded NTU severity bars.

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🔧 Installation & Setup

1. Prerequisites

Ensure you have Python 3.8+ installed.

2. Install Dependencies

pip install opencv-python numpy matplotlib reportlab scikit-image scipy

3. Run the Application

python turbidity_gui.py

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🛠️ Technologies Used

• OpenCV: Core image processing and feature extraction.
• Tkinter: Graphical User Interface.
• Matplotlib: Data visualization and histogram plotting.
• ReportLab: PDF report generation.
• NumPy/SciPy/Scikit-Image: Numerical computing and advanced image analysis.