Machine learning based text identification method of identity card image

A text recognition and machine learning technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of low recognition accuracy, long recognition time, poor distortion, etc., and achieve high recognition accuracy, recognition short time effect

Inactive Publication Date: 2017-10-13
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

[0013] The present invention provides a machine learning-based ID card image text recognition method for the above shortcomings, which solves the problem of long recognition time and low recognition accuracy in the prior art when OCR recognition automatically recognizes ID card images under complex backgrounds. , anti-rotation, poor twisting problems

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  • Machine learning based text identification method of identity card image
  • Machine learning based text identification method of identity card image

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Embodiment Construction

[0044] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0045] A machine learning-based ID card image text recognition method is characterized in that it comprises the following steps:

[0046] Step 1. Obtain the captured image, preprocess the captured image, and distinguish the ID card image from the complex background image in the preprocessed image; the specific steps are as follows:

[0047] (11), using Gaussian blur and grayscale to preprocess the captured image;

[0048] (12), step (11) is carried out to the image after preprocessing, use Canny operator and Sobel operator to carry out ID card edge detection;

[0049] (13), using binarization and...

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Abstract

The invention discloses a machine learning based text identification method of an identity card image belongs to the technical fields including image processing, machine vision and neural network, and solves the problems of long identification time, low identification accuracy and low rotation and distortion resistance when OCR in the prior art is used to identify identity card images automatically in a complex background. The method comprises that a shot image is obtained and preprocessed, and the identity card image is separated from a complex background image in the preprocessed image; character area detection is carried out on the detected identity card image, and character cutting is carried out on a detected text area to obtain single characters; and a deep learning based character identification model is used to identify the cut characters, and an identification result is output. The method can be used to identity text in the identity card image.

Description

technical field [0001] A machine learning-based text recognition method for ID card images is used for text recognition on ID card images, and belongs to the technical fields of image processing, machine vision, and neural networks. Background technique [0002] Document recognition is to use Optical Character Recognition (OCR, Optical Character Recognition) technology to identify the text information on the document. Specifically, it refers to the process of using OCR technology to analyze and recognize the scanned and photographed document images to obtain the text information on the document. Compared with the traditional manual input method, OCR's automatic information input has huge advantages. It is far superior to human work efficiency in terms of speed and accuracy, especially when people are fatigued with the increase of working hours. Not only does the speed of entering information decrease, but the accuracy rate also naturally decreases. Human beings are natural...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/20G06K9/46G06K9/62
CPCG06V10/22G06V10/44G06F18/2411G06F18/214
Inventor 屈鸿黄鹂高榕刘永胜张翮史冬霞陈珊汪一文
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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