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Text positioning box correction method and system based on convolutional neural network

A convolutional neural network and text positioning technology, which is applied in biological neural network models, neural architectures, instruments, etc., can solve the problems of unframed text, insufficient precision, and text included, so as to reduce uniform size and reduce the amount of calculation. , targeted effect

Pending Publication Date: 2020-10-16
厦门商集网络科技有限责任公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the prior art, when some text positioning methods are used for text positioning of text pictures, the phenomenon of blurred and inaccurate text positioning boundaries will appear. Most of this phenomenon is that the text positioning box cannot completely locate all the text; The anchor box is too large and contains irrelevant text
Although these positioning methods can locate most of the required text, the positioning at the corners of the four vertices of the text area still has insufficient precision. The height of each text may be different. Sometimes the required text cannot be completely surrounded by the rectangular text positioning box, and a small part of the text will not be framed; (2) Some symbols without text meaning in the document file will be regarded as text positioning
Inaccurate text positioning has a negative impact on the subsequent text recognition work, directly affecting the accuracy of the recognition results, resulting in incorrect results

Method used

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  • Text positioning box correction method and system based on convolutional neural network
  • Text positioning box correction method and system based on convolutional neural network
  • Text positioning box correction method and system based on convolutional neural network

Examples

Experimental program
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Effect test

Embodiment 1

[0063] Such as figure 1 As shown, the text positioning frame correction method based on the convolutional neural network includes the following steps:

[0064] S1: Obtain multiple text images to be located.

[0065] S2: Input the acquired multiple text images to be positioned into the text detection model, the text detection model performs rough text positioning on the text images to be positioned, and outputs the positioned text images and the text positioning frame to be corrected The coordinate values ​​of the four upper and lower endpoints at the left and right ends of .

[0066] Such as figure 2 As shown, this picture is a text image, that is, an image with text. The rectangular frame is the text positioning frame obtained by the text detection model through rough positioning. It can be seen that the upper part of the text positioning frame does not include the upper part of all the text, which will lead to subsequent recognition errors. The corner points marked by t...

Embodiment 2

[0115] The text positioning frame correction system based on the convolutional neural network includes a memory and a processor, the memory stores instructions, and the instructions are suitable for being loaded by the processor and performing the following steps:

[0116] S1: Obtain multiple text images to be positioned.

[0117] S2: Input the acquired multiple text images to be positioned into the text detection model, the text detection model performs rough text positioning on the text images to be positioned, and outputs the positioned text images and the text positioning frame to be corrected The coordinate values ​​of the four upper and lower endpoints at the left and right ends of .

[0118] S3: Establish a text positioning frame correction model, and train the text positioning frame correction model.

[0119] S4: After cropping and scaling the text positioning frame to be corrected and its corresponding image content, input the trained text positioning frame correctio...

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Abstract

The invention relates to a text positioning box correction method and system based on a convolutional neural network, and the method comprises the steps: building a neural network for text positioningbox correction, carrying out the independent training of the left and right ends of a text positioning box, setting a subsequent verification step for verifying a result, and guaranteeing that a trained model meets the requirements. Compared with the prior art, the text box correction model obtained by training is used for correcting the text positioning box in the text picture, so that the positioning precision of the text detection method can be effectively improved, a more accurate text positioning box is obtained, and the accuracy of picture text recognition and the practicability of a text detection and recognition system are improved.

Description

technical field [0001] The invention relates to a text positioning frame correction method and system based on a convolutional neural network, and belongs to the field of OCR text recognition. Background technique [0002] OCR (optical character recognition) character recognition refers to the process in which electronic devices (such as scanners or digital cameras) check the characters printed on paper, and then use character recognition methods to translate the shape into computer text; that is, the text data is scanned, and then The process of analyzing and processing image files to obtain text and layout information. With the advancement of image processing technology in recent years, there is an increasing demand for OCR text recognition. In the OCR text recognition process, the most basic step is to accurately locate the text in the image. Only by completing accurate positioning can the subsequent recognized text be correct and without omissions. At present, the two ...

Claims

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Application Information

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IPC IPC(8): G06K9/20G06K9/32G06K9/62G06N3/04
CPCG06V10/24G06V10/22G06V30/10G06N3/045G06F18/214
Inventor 茹超飞黄征
Owner 厦门商集网络科技有限责任公司
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