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Recognition method, system and electronic equipment for Uyghur handwritten letter

A recognition method and recognition system technology are applied in the field of Uyghur handwritten letter recognition methods, systems and electronic equipment to achieve the effects of improving performance, high recognition accuracy and avoiding overfitting.

Active Publication Date: 2018-10-16
XINJIANG UNIVERSITY
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Problems solved by technology

[0005] Deep learning has demonstrated its advantages in many fields of pattern recognition, and thus has received extensive attention and applications [Alom M Z, Sidike P, Hasan M, et al. Handwritten Bangla Character Recognition Using The State-of-Art Deep Convolutional Neural Networks[J].2017.], but there is no relevant research on the recognition of Uyghur handwritten letters using deep learning technology

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  • Recognition method, system and electronic equipment for Uyghur handwritten letter
  • Recognition method, system and electronic equipment for Uyghur handwritten letter
  • Recognition method, system and electronic equipment for Uyghur handwritten letter

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Embodiment Construction

[0058] In order to make the purpose, technical solution and advantages of the present application clearer, the present application 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 application, not to limit the present application.

[0059] Aiming at the problem of recognition of Uyghur handwritten letters existing in the prior art, this application uses deep learning methods to conduct handwriting recognition research on 128 writing forms of Uyghur letters, and converts the preprocessed online Uyghur handwritten letter samples into binary images, Then the convolutional neural network is used for automatic feature extraction and classification, and different network structures and configurations are used to recognize letter images of different sizes.

[0060] Specifically, see figure 1 , is a flow chart of the Uyghur ...

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Abstract

The application belongs to the technical field of character recognition, and particularly relates to a recognition method, system and electronic equipment for Uyghur handwriting letters. The recognition method for Uyghur handwriting letters comprises the following steps of: step a, collecting / reading / reading an original handwriting sample of Uyghur letters; step b, preprocessing the original handwriting sample, and converting the original handwriting sample into a binary image; and step c, inputting the binary image into a convolutional neural network for classification training and testing to obtain an recognition result of the original handwriting sample. According to the recognition method, system and electronic equipment of Uyghur handwriting letters, the performance of the networkmodel is effectively improved, and the identification accuracy is high.

Description

technical field [0001] The present application belongs to the technical field of character recognition, and in particular relates to a Uighur handwritten letter recognition method, system and electronic equipment. Background technique [0002] Handwriting recognition is one of the most typical applications of pattern recognition [Gao Y, Jin L, He C, et al. Handwriting Character Recognition as a Service: A New Handwriting Recognition System Based on Cloud Computing [J]. 2011: 885-889.]. From the earliest applications of number and address checking in postal and banking services, to the digitization of historic resources in libraries and museums, handwriting recognition has been popular in offices, automation and everyday communications. Currently, it is one of the most popular attributes of human-computer interactive smart devices. There are two main branches of handwriting recognition, which are online handwriting recognition and offline handwriting recognition[Liu C L, Yin...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06K9/62G06N3/04
CPCG06V30/153G06N3/045G06F18/241G06F18/214
Inventor 艾斯卡尔·艾木都拉吾加合买提·司马义玛依热·依布拉音
Owner XINJIANG UNIVERSITY
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