README.md

# Corrosion Detection System:

• Central Control Unit: The system uses a Raspberry Pi 4 as the main control unit.

• Camera Module: Equipped with a Raspberry Pi Camera Module for live video streaming and capturing footage of target areas.

• Servo Motors: Includes two servo motors (SG90 and MG996R) for precise camera movement, allowing 180-degree horizontal and vertical panning.

• Motor Driver Unit: Controls the propulsion of the ROV and the movement of the camera.

• Algorithm Execution: Raspberry Pi runs a morphological algorithm using Python and OpenCV libraries to analyze live video feeds for signs of corrosion.

• Detection Criteria: The algorithm identifies corrosion based on discoloration and texture irregularities.

• Real-time Feedback: Detected corrosion instances are displayed immediately on a screen.

• Remote Access: Remote monitoring and control are possible through the RealVNC Viewer application, allowing operators to adjust the camera orientation and view the live feed.

• Power Supply: Uses LM2596 DC-DC step-down power supply modules to convert a 12V DC input to a 5V DC output, ensuring stable power for the Raspberry Pi and servo motors.

• Safety Features: LM2596 modules offer overcurrent protection, thermal shutdown, and reverse polarity protection.

• Compact Setup: All components are integrated into the ROV chassis for a streamlined and efficient configuration.

• Image Processing: Converts RGB images to HSV color space to effectively identify corrosion.

• Color Range Definition: Sets specific HSV color ranges to detect corrosion areas accurately.

• Binary Mask Creation: Generates a binary mask to highlight corroded regions in white.

• Contour Detection: Uses contour detection algorithms to visualize and delineate corroded areas, aiding in proactive maintenance.

# System and sample output:

Above is the complex structure of Tanks in Merchant ships.

Circuit Diagram of our system

This is our Entire system for detection of corrosion.

Live Corrosion detection.