• Shashikant Vishwakarma
• Ritu Sharma

Shipping containers are crucial for global trade. However, they can suffer damage during transportation that can result in significant losses for both shippers and customers. In this research paper, I propose an automated damage detection system for shipping containers based on image processing techniques. The system analyses images captured by cameras installed in cargo ships and ports to identify any signs of damage on the container's exterior. The proposed system uses a convolutional neural network to analyse the images and detect various types of damage such as scratches, dents, and cracks. The results show that our proposed system has a high accuracy rate in detecting and classifying different types of damage. Using our system, shipping companies can quickly identify any damage to containers and take appropriate measures to minimize any further damage, reducing the risk of cargo loss. This system can help to improve the efficiency and safety of shipping operations and can result in significant cost savings for companies.

Image processing, damage detection, shipping containers, convolutional neural network, cargo loss, cost savings.

"Automated Damage Detection in Shipping Containers using Image Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.j443-j448, July-2023, Available :http://www.jetir.org/papers/JETIR2307957.pdf

"Automated Damage Detection in Shipping Containers using Image Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppj443-j448, July-2023, Available at : http://www.jetir.org/papers/JETIR2307957.pdf