BP neural network-based steel seal character recognition method

A BP neural network and character recognition technology, which is applied in the field of stencil character recognition based on BP neural network, can solve the problems of poor image threshold segmentation, uneven lighting, and noise.

CN110929713AActive Publication Date: 2020-03-27CENT SOUTH UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2020-03-27

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Abstract

The invention discloses a BP neural network-based steel seal character recognition method, which belongs to the technical field of image recognition. The method comprises the following steps of: photographing a workpiece steel seal through an industrial camera arranged in an industrial field, and acquiring an image; performing threshold segmentation on the image through a machine learning clustering algorithm. A good segmentation effect is achieved; the problem that features and character backgrounds cannot be accurately segmented through traditional single threshold segmentation for steel seal pictures is solved. Meanwhile, a clustering algorithm is applied to character segmentation, automatic segmentation of characters in the image is achieved, normalization processing of the image solves the problem that the size of the image is changed due to the fact that position deviation possibly exists in the moving process of the workpiece, and the accuracy of steel seal recognition is improved; meanwhile, training of the steel seal recognition model is achieved through the neural network, and the model has a good effect in a test set.
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Description

technical field

[0001] The invention belongs to the technical field of image recognition, and in particular relates to a steel stamp character recognition method based on a BP neural network. Background technique

[0002] In recent years, due to the rapid development of computer technology and sensor technology, traditional factories have gradually developed in the direction of intelligence and unmanned. However, during the processing of large castings and aluminum parts, the surface of the workpiece The temperature can reach hundreds of degrees Celsius, so it cannot be automatically identified by traditional RFID (such as two-dimensional codes, sensors, etc.) In some cases, there will be problems such as slow input speed and incorrect input results. Therefore, in order to realize the intelligent upgrading of the factory and solve the problems existing in the automatic identification of factory materials, an image recognition technology is urgently needed to realize the auto...

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Embodiment Construction

[0081] The present invention will be further described below in conjunction with specific embodiment and accompanying drawing:

[0082] The embodiment of the present invention is a kind of steel seal character recognition method based on BP neural network, such as figure 1 shown, including the following steps:

[0083] (1), image acquisition: image acquisition is taken by a CCD industrial camera fixed on the industrial site, such as figure 2 As shown, the distance between it and the surface of the workpiece is basically fixed, and the distance may fluctuate in a small range with the difference in the placement of the workpiece;

[0084] (2) Image grayscale conversion: By reading the R, G, and B values ​​of the picture pixels, the grayscale value Through the above operations, the color image is converted into a grayscale image;

[0085] (3) Use Gaussian filtering to smooth and denoise the image. The smoothness depends on the standard deviation. Its output is the weighted a...