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
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[0062] Example one
[0063] Such as figure 1 As shown, the text positioning frame correction method based on convolutional neural network includes the following steps:
[0064] S1: Obtain multiple text images to be located.
[0065] S2: Input a plurality of acquired text images to be positioned into a text detection model, the text detection model performs coarse text positioning on the text image to be positioned, outputs the positioned text image, and a text positioning frame to be corrected The coordinates of the upper and lower ends of the left and right ends.
[0066] Such as figure 2 As shown, this picture is a text image, that is, an image with text. The rectangular box is the text positioning box obtained by the text detection model after rough positioning. It can be seen that the upper part of this text positioning box does not include the upper part of all the text, which will cause subsequent recognition errors. The corner points marked by the four dots are the four poin...
Example Embodiment
[0114] Example two
[0115] A text positioning frame correction system based on a convolutional neural network includes a memory and a processor. The memory stores instructions, and the instructions are adapted to be loaded by the processor and execute the following steps:
[0116] S1: Obtain multiple text images to be located.
[0117] S2: Input a plurality of acquired text images to be positioned into a text detection model, the text detection model performs coarse text positioning on the text image to be positioned, outputs the positioned text image, and a text positioning frame to be corrected The coordinates of the upper and lower ends of the left and right ends.
[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 box to be corrected and its corresponding image content, input the trained text positioning box correction model, output the correction value...
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