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Identification method for handwritten numbers

A recognition method and digital technology, applied in the field of optical recognition, to achieve the effect of improving the accuracy and recognition rate

Pending Publication Date: 2018-11-02
TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for recognizing handwritten digits, which can improve the accuracy and recognition rate of handwritten digit recognition under similar complexity

Method used

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  • Identification method for handwritten numbers

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Embodiment Construction

[0031] Embodiments of the present invention are described in further detail below in conjunction with the accompanying drawings:

[0032] A method for recognizing handwritten digits, comprising the following steps:

[0033] Step 1. Preprocessing the digital image by using the preprocessing digital image module. Preprocessing includes the following steps:

[0034] (1) Grayscale digital image step.

[0035] The solution to grayscale digital images is based on the concept of YUV, where brightness can be represented by Y, and its value can reflect the brightness level of the image. Then through the connection between YUV and RGB to obtain the corresponding relationship between Y and the three channels of the image R, G, and B: Y=0.3R+0.59G+0.11B. Finally set this Y value to the pixel value of the image. The new image obtained by the above processing is the grayscale image required by this embodiment, as figure 1 shown.

[0036] (2) The step of binarizing the digital image. ...

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PUM

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Abstract

The invention relates o an identification method for handwritten numbers. The method comprises the following steps of preprocessing number images, wherein the preprocessing step comprises the substepsof graying the number images, carrying out binaryzation on the number images, carrying out image denoising, segmenting character strings, carrying out number normalization, and carrying out number refinement; and setting up a deep convolutional neural network model, configuring neural network parameters, generating training set samples and test set samples, adjusting the parameters, training thenetwork model, and identifying the numbers through the trained network mode. According to the method, through preprocessing of the image, influences of noises on the image can be prominently reduced,and the images with different sizes can be normalized into the images with the same size; through utilization of the deep convolutional neural network, the training set samples and the test set samples are generated, the parameters are adjusted, the network is trained, and the numbers are identified through utilization of the trained network model. The handwritten number identification accuracy and rate can be improved under the condition that the complexity is similar, and the method can be widely applied to the fields such as post office letter sorting and bank check inputting.

Description

technical field [0001] The invention belongs to the technical field of optical recognition, in particular to a method for recognizing handwritten numbers. Background technique [0002] The technology of recognizing handwritten digits is one of the branches of optical character recognition, which can intelligently recognize digits on various texts with the help of machines or computers. Since all countries use the same number, and people's demand for informatization is increasing, the application prospect of handwritten number recognition in large-scale data analysis systems such as post office letter sorting and bank check entry is very broad. [0003] At present, there are mainly two kinds of recognition of handwritten digits, one is recognition based on its structural characteristics, and the other is recognition based on statistical characteristics. Countries around the world have made great achievements in research in this direction. For example, in order to meet the ne...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06K9/40G06K9/44G06K9/62G06N3/04
CPCG06N3/04G06V30/153G06V10/267G06V10/30G06V10/34G06F18/214
Inventor 梁倩杜程
Owner TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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