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Off-line handwritten Chinese character font recognition method based on deep convolutional neural network

A technology of convolutional neural network and recognition method, which is applied in the field of offline handwritten Chinese font recognition, can solve problems such as poor recognition effect, and achieve the effect of improving recognition effect and high recognition accuracy

Inactive Publication Date: 2018-11-06
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the shortcomings of the poor recognition effect of existing offline handwritten Chinese font recognition methods, the present invention provides an offline handwritten Chinese font recognition method based on a deep convolutional neural network to improve the recognition effect

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  • Off-line handwritten Chinese character font recognition method based on deep convolutional neural network
  • Off-line handwritten Chinese character font recognition method based on deep convolutional neural network
  • Off-line handwritten Chinese character font recognition method based on deep convolutional neural network

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Embodiment Construction

[0027] The present invention will be further described below in conjunction with the accompanying drawings.

[0028] refer to figure 1 and figure 2 , an offline handwritten Chinese font recognition method based on a deep convolutional neural network, comprising the following steps:

[0029] 1) Acquisition and reading of Chinese character images;

[0030] 2) Process the image, the process is as follows:

[0031] 2.1) First of all, Chinese characters must be segmented, and all Chinese characters in the picture should be divided into one picture and one Chinese character;

[0032] 2.2) Then compress or enlarge the image, because the segmented image may not meet the recognition input, so the image needs to be normalized, and the unified size is 64*64 pixels;

[0033] 3) Read in the processed picture group, use the trained deep convolutional neural network to identify, and output the result;

[0034] The deep convolutional neural network includes 3 convolutional layers, 3 poo...

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Abstract

The invention provides an off-line handwritten Chinese character font recognition method based on a deep convolutional neural network. The off-line handwritten Chinese character font recognition method includes the following steps: 1) collecting and reading Chinese character images; 2) processing the images, including the following steps: 2.1) segmenting the Chinese characters, segmenting all theChinese characters in the images into one Chinese character for one image; and 2.2) compressing or zooming the images, performing normalization on the images as the segmented images cannot satisfy input of recognition, wherein the unified size is 64*64 pixel; and 3) reading the processed image group, performing recognition through the trained deep convolutional neural network, and outputting the result. The off-line handwritten Chinese character font recognition method based on a deep convolutional neural network can improve the recognition effect.

Description

technical field [0001] The invention belongs to the technical field of image classification, in particular to an off-line handwritten Chinese font recognition method based on a deep convolutional neural network Background technique [0002] Offline handwritten Chinese character recognition is a sub-direction in the field of pattern recognition. Offline means that the handwritten text to be processed is a two-dimensional image of the handwritten text collected by an image capture device such as a scanner or a camera. In the field of handwriting research, Casey and Nag successfully recognized 1000 printed Chinese characters using template matching in 1966. In the late 1970s, the research on offline handwritten Chinese character recognition has attracted widespread social attention. Different from English recognition, Chinese character recognition is very difficult. The difficulties include the following points: there are many types of Chinese characters (there are more than ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/34G06K9/62G06N3/04
CPCG06V30/153G06V10/267G06N3/045G06F18/241G06F18/214
Inventor 陆成刚黄成斌
Owner ZHEJIANG UNIV OF TECH
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