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Image classification method and device, electronic equipment and storage medium

A classification method and image technology, applied in the computer field, can solve problems such as time-consuming, low development efficiency, and difficulty in obtaining images

Pending Publication Date: 2020-10-30
CHINA CONSTRUCTION BANK
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

First of all, the existing methods need to collect a large number of sample pictures as training data, but in real application scenarios, due to reasons such as data confidentiality, it is difficult to obtain a sufficient number of pictures, so the accuracy of the image classification model for targeted training is not high; secondly, The existing method needs to train a targeted deep learning model, which usually takes a long time and has low development efficiency; finally, the deep learning model trained by the existing method can only judge one type of picture, and adding a new picture type requires re-collecting data, Label data and train models, so this method is not very versatile

Method used

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  • Image classification method and device, electronic equipment and storage medium
  • Image classification method and device, electronic equipment and storage medium
  • Image classification method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] figure 1 It is a flow chart of an image classification method provided by Embodiment 1 of the present invention. This embodiment is applicable to the case of classifying images through templates. This method can be executed by the image classification device provided by the embodiment of the present invention. The device can Realized by software and / or hardware. see figure 1 , the image classification method provided in this embodiment includes:

[0055] Step 110, acquiring all character strings in the image to be classified.

[0056] Wherein, the image to be classified is a text image, for example, it may be a reimbursement form, a leave form, and the like.

[0057] Obtain the text content of all text parts in the image to be classified, and store it in the form of a string. The text content includes picture titles and field names, and may also include specific content filled in after the field names, which is not limited in this embodiment.

[0058] figure 2 It...

Embodiment 2

[0085] image 3 It is a flow chart of an image classification method provided by Embodiment 2 of the present invention, and this technical solution is a supplementary explanation for the process of classifying images according to the matching degree. Compared with the above scheme, the specific optimization of this scheme is to classify the images according to the matching degree, including:

[0086] If the matching degree is greater than a preset threshold, it is determined that the image to be classified matches the template image;

[0087] The template category associated with the template image is determined as the type of the image to be classified. Specifically, the flow chart of the image classification method is as follows image 3 Shown:

[0088] Step 310, acquiring all character strings in the image to be classified.

[0089] Wherein, the image to be classified is a text image, for example, it may be a reimbursement form, a leave form, and the like.

[0090] Obt...

Embodiment 3

[0111] Figure 4 It is a schematic structural diagram of an image classification device provided by Embodiment 3 of the present invention. The device can be implemented by hardware and / or software, can execute an image classification method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. Such as Figure 4 The device includes:

[0112] The first character string obtaining module 410, is used for obtaining all character strings in the image to be classified;

[0113] The phrase to be matched determining module 420 is used to determine the phrase to be matched according to the text string; wherein, the phrase to be matched is composed of a continuous preset number of characters in the text string;

[0114] Matching degree determining module 430, is used for described phrase to be matched and the phrase match in the template vocabulary, to determine the matching degree of described ph...

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Abstract

The embodiment of the invention discloses an image classification method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining all character strings in a to-be-classified image; determining a phrase to be matched according to the character string, wherein the phrase to be matched is composed of a preset number of continuous characters in the character string; matching the to-be-matched phrases with phrases in a template word list to determine the matching degree of the to-be-matched phrases and the phrases in the template word list; and classifyingthe images according to the matching degree. By operating the technical scheme provided by the embodiment of the invention, the problems of low accuracy of an image classification model trained by anexisting method in a targeted manner, time consumed for training the targeted deep learning model is long, the development efficiency is low, only one type of picture can be judged, and the universality is not high are solved, and the effect of improving the accuracy, efficiency and universality of image classification is achieved.

Description

technical field [0001] The embodiments of the present invention relate to computer technology, and in particular to an image classification method, device, electronic equipment and storage medium. Background technique [0002] With the development of computer technology, image classification is often done through image recognition technology. [0003] At present, image classification technology based on deep learning is mainly used to judge the image type. First of all, the existing methods need to collect a large number of sample pictures as training data, but in real application scenarios, due to reasons such as data confidentiality, it is difficult to obtain a sufficient number of pictures, so the accuracy of the image classification model for targeted training is not high; secondly, The existing method needs to train a targeted deep learning model, which usually takes a long time and has low development efficiency; finally, the deep learning model trained by the existin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06V10/751G06F18/24
Inventor 胡雅伦郑邦东车越云
Owner CHINA CONSTRUCTION BANK