Convolutional neural network classification-based container number recognition method

Abstract

The invention discloses a convolutional neural network classification-based container number recognition method. The method comprises the following steps of: S1, obtaining RGB images of a container indifferent directions, carrying out a series of preprocessing on the RGB images so as to locate container number areas in the images; S2, carrying out perspective transformation and binarization on the located container number areas in the step S1, and correctly segmenting various container number characters through a character border and projection method combined processing method; and S3, inputting the segmented container number characters in the step S2 into a preset five-layer convolutional neural network model according to a sequence of positions of the container number characters in thecontainer number, combining recognition results, and carrying out post-processing to obtain a correct container number. The method is capable of correctly solving various problems such as character deformation, incompletion and adhesion, and realizing higher recognition correctness and speed.

Description

technical field [0001] The invention relates to an image processing method, which belongs to the technical field of image processing, in particular to a container number recognition method based on convolutional neural network classification. Background technique [0002] With the advancement of science and technology and the huge growth of trade among countries around the world, the logistics and transportation industry has accelerated its development year by year, and the global shipping volume has hit new highs year by year. As the main transportation and loading method of ocean transportation, containers play a very important role in ocean transportation. While shipping is booming, the management of containers requires more modern means to achieve the purposes of tracking a huge number of containers, cargo transfer and cargo ship storage planning. [0003] The container number is the unique identification code of each container. Automatic identification of the container...

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Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies and defects in the prior art, and provide a container number recognition method based on convolutional neural network classification. The good classification performance of the convolutional neural network can classify and recognize various extracted characters, and can deal with problems such as deformation, incompleteness, and adhesion of various characters, and achieve higher recognition accuracy and recognition speed

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