Method, device, readable storage medium, and terminal for detecting increase or decrease of certificate types

Abstract

The invention provides a method, a device, a readable storage medium and a terminal for detecting the increase or decrease of a certificate. The method firstly stores standard pictures of various types of certificates in a memory as a registered picture; secondly, detects the certificate to be detected, obtains an input picture, and treats the certificate to be detected. The input picture undergoes image processing; finally, the processed picture is compared with the registered picture, and the category of the detected picture is determined by the similarity, so as to quickly and efficiently screen the new certificate to determine the category. The detection scheme can improve the accuracy and efficiency of judging new document types in complex shooting scenarios, and can be widely used in security, finance and other fields.

Description

technical field [0001] The present invention relates to the technical field of information detection or intelligent vision, and in particular to a method, device, readable storage medium and terminal for detecting an increase or decrease category of a certificate. Background technique [0002] For document image recognition, it is necessary to quickly and efficiently identify identity information in the fields of security, finance, and enterprise information management. In the early days, most of the information of ID cards required manual input, which was very inefficient, and the long-term identification process would also make people's eyes tired. [0003] With the rise of artificial intelligence, image recognition technology is gradually applied in security, military, medical, intelligent transportation and other fields, and technologies such as face recognition and fingerprint recognition are increasingly used in public security, finance, aerospace and other security fi...

AI Technical Summary

Problems solved by technology

This method is currently a popular character detection method, but for the document number detection task, this method has the following defects: (1) Non-document area images also participate in the network reasoning process, which wastes computing resources on the one hand, and on the other hand, for non-document Misdetection of character presence in the region requires additional processing logic to eliminate; (2) The calculation resource consumption of this scheme is relatively large, and the training and reasoning time is longer than this proposal; (3) Due to the uninterpretable behavior of the neural network, this method The frame of the positioned character area cannot accurately locate the smallest circumscribed rectangular frame of the character, and even part of the character area will be cut off. That is, the traditional document image optical recognition (OCR) technology is mainly for high-definition scanned images. This method requires the recognized image to have a clean background, use standard typography and have high resolution

However, in natural scenes, there are problems such as large text background noise, irregular text distribution, and the influence of natural light sources. The detection rate of OCR technology in actual natural scenes is not ideal, and the recognition of documents such as documents will bring pressure to character recognition in subsequent steps.

[0006] In addition, although AI technology has been applied in all walks of life and can meet the needs of some actual application scenarios, as the targets to be detected or identified, such as customer detection targets in the banking industry, are added or deleted from time to time, detection When the target increases, it is often necessary to complete sample collection, labeling, model training, deployment, etc., and the optimization process takes a long time and is inefficient

[0007] Based on the above situation, in the intelligent detection of documents (including ID cards, bank cards, work permits, etc.)

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