OCR for Yard Crane

1.Function Introduction

Based on artificial intelligence visual analysis, at various stages and processes of port operations, identify and report the truck number, container number, ISO code, container door, lead seal, dangerous goods mark, damage and other situations.  

2.Technical indicators

The accuracy of container number recognition is greater than 99%, and the accuracy of vehicle number recognition is greater than 99.6%;

Support video streaming and capture recognition, with a single recognition time of less than 100 milliseconds;

Suitable for container and vehicle identification on shore bridges, gates, and yard bridges, supporting container damage detection;

Scalable as an intelligent cargo handling system under the quay crane, providing container data to TOS

3.system function

Container number intelligent recognition, container door recognition, vehicle recognition, roof number recognition

4.System advantages

Accurate positioning and segmentation

Perform a series of algorithms such as grayscale, noise filtering, edge enhancement and extraction, texture feature analysis, etc. on the original image to accurately locate and segment container numbers; Strong anti-interference ability, adaptable to various weather and lighting conditions.

Neural Network Algorithm

The use of the latest artificial intelligence algorithm - Convolutional Neural Network algorithm for character segmentation recognition not only improves the accuracy of image recognition, but also avoids the time consumption of manually extracting features, thereby greatly improving computational efficiency. In cases of uneven wear, paint peeling, and high noise, the recognition rate is significantly better than that of general OCR systems.