Bill number identification method and system based on deep neural network

A technology of deep neural network and recognition method, applied in the direction of neural learning method, biological neural network model, neural architecture, etc., can solve problems such as recognition, achieve the effect of ensuring experimental results, realizing lightweight models, and realizing real-time work

Pending Publication Date: 2021-05-04
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0004] The present invention proposes a bill quantity recognition method and system based on a deep neural network to solve the problem of how to quickly identify the bill quantity of an image

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  • Bill number identification method and system based on deep neural network
  • Bill number identification method and system based on deep neural network
  • Bill number identification method and system based on deep neural network

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Embodiment Construction

[0043]Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for the purpose of this thorough and complete disclosure invention, and fully convey the scope of the invention to those skilled in the art. The terms used in the exemplary embodiments shown in the drawings are not intended to limit the invention. In the drawings, the same elements / elements are given the same reference numerals.

[0044] Unless otherwise defined, terms (including scientific and technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is to be understood that terms defined in commonly used dictionaries should be construed as having meanings consistent with the context in the related art, and should not be construed as idealized or overly formal ...

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Abstract

The invention discloses a bill number identification method and system based on a deep neural network, and the method comprises the steps: sequentially carrying out the graying processing, binarization processing, normalization processing and two-dimensional image mapping one-dimensional data processing of an obtained two-dimensional mixed-shot bill original image, and greatly reducing the data size while maintaining the image information. Time waste caused by data transmission is reduced, and user experience is improved; by designing an OCTC model, introducing a one-dimensional convolution operation to perform feature extraction and image category calculation on image data, and using a plurality of small-size convolution kernels to increase a model receptive field, the experimental effect is ensured, the model parameter quantity is reduced, the effect of a lightweight model is realized, and storage and use by a user are facilitated; according to the method, the user can receive the judgment result of the number of bills in the image while uploading the image, the user experience of a mixed shooting bill recognition system is improved, meanwhile, the system is helped to carry out subsequent bill target detection and content recognition tasks, and real-time work of the system is achieved.

Description

technical field [0001] The present invention relates to the technical field of bill processing, and more particularly, to a method for identifying the number of bills based on a deep neural network. Background technique [0002] The method for identifying the number of bills is used in the bill pre-judgment stage in the initial stage of the mixed-shot bill identification system. At present, bill recognition on the market is mainly based on AlexNet, Fast-RCNN, OCR and other technologies to identify bill information in images. Such methods have good stability and performance after long-term use and verification. The fixedness leads to limited application and cannot be adjusted according to the actual situation. In addition, the bill recognition system analyzes bills by introducing target detection operations. Due to the overlapping, tilting, and low resolution problems of bills shot in real scenes, this will affect the area that can be detected by the model, thereby reducing ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06N3/045G06F18/2415G06F18/241
Inventor 徐书豪金洪亮梅俊辉王芳闫凯王志刚林文辉
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