Intelligent detecting and evaluating method for container number preprocessing quality of containers

Abstract

The invention provides an intelligent detecting and evaluating method for container number preprocessing quality of containers. The intelligent detecting and evaluating method comprises the following steps of firstly, performing Canny operator edge detection on a preprocessed image; secondly, screening images with container numbers possibly in an integral jumping frequency detecting and evaluating mode; thirdly, detecting and evaluating a unilateral projection distribution model to record positions of similar container number regions; fourthly, detecting and evaluating a bilateral jumping model and circularly detecting and evaluating a local connection region on the similar container number regions; and finally, performing examination based on U characters according to screened-out regions so as to accurately judge whether container numbers exist in the positions or not and whether a preprocessing effect is ideal or not. Reasons for failure are analyzed in the detecting and evaluating stages. By the method, after the images are detected and evaluated, whether recognition is carried out continuously or the container number preprocessing quality is reprocessed by another technology can be determined automatically. The preprocessing images can be optimum before positioning of the container numbers, and recognition failure caused by complex environments is reduced.

Description

technical field [0001] The invention is applied in the image processing field of the container number recognition system, mainly intelligently evaluates the quality of the container number preprocessing, and automatically circulates and reprocesses the technology according to the evaluation result. Background technique [0002] Containers are the main transportation equipment for international logistics, and 90% of international freight is done through container transportation. The container number is the unique identifier of the container and plays a very important role in container management. At present, the yard management and loading and unloading management of many container terminals in my country have been computerized, but the container number identification at the gate of the container terminal, container cranes, bridge cranes, etc. still relies on the identification of human eyes. The labor cost is high, the work efficiency is low, and the boring manual identific...

AI Technical Summary

Problems solved by technology

[0005] The above-mentioned processing techniques have very large limitations in complex environments, and it is difficult to be effective for all images through a single preprocessing

Image processing technologies such as grayscale, enhancement, and binarization are very sensitive to the brightness of the light and the complexity of the surrounding environment of the box number; the image processing technology cannot have an automatic adaptation threshold due to daytime and night light and light exposure. ; Interferences such as stains around the box number and other useless information often make the preprocessing result ignore the box number information

Such a result will lead to positioning failure or positioning error, let alone complete recognition

Images