Image-based verification code implementation method and device

Abstract

The embodiment of the invention provides an image-based verification code implementation method and device. Malicious machine accessing can be effectively prevented, and implementation is easy and operation is easy and convenient. The image-based verification code implementation method comprises the steps that the first number of forward images of which the direction is identifiable are randomly extracted from an image library, and the second number of images are randomly selected from all the extracted forward images to be rotated; the first number of images are spliced into two-dimensional matrix verification images, and position relation information of the rotated images is correspondingly recorded; when a verification request is received, one spliced two-dimensional matrix verification image and the position relation information of the rotated images are acquired; the two-dimensional matrix verification image is returned to a client side to be displayed; and the position relation information of the clicked image of the user in the two-dimensional matrix verification image transmitted by the client side is received and compared with the position relation information of the rotated images, and whether verification of the user is passed is judged according to the comparison result.

Description

technical field [0001] The invention belongs to the field of network security, and in particular relates to a method and device for realizing a verification code based on a picture. Background technique [0002] Verification code, also known as CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart, fully automatic public Turing test to distinguish between computers and humans), is a public fully automatic program to distinguish whether the user is a machine or a human. In the prior art, the mainstream verification code implementation method usually adopts the form of a combination of characters and picture backgrounds, and may add certain interference pixels at the same time, and prevent malicious access to the machine by identifying the content of the verification code input by the user. [0003] Nowadays, OCR (Optical Character Recognition, Optical Character Recognition) technology has developed very maturely. OCR technology converts the text ...

AI Technical Summary

Problems solved by technology

For ordinary character pictures, it is easy to recognize the characters on the picture verification code. Although the automatic recognition of the machine is interfered with by additional interference factors, such as adding random pixels, random lines and random picture distortions on the picture, but in this way Not only did not prevent the machine from automatically recognizing the characters on the picture, but it made it difficult for normal users to see the characters on the picture, which increased the user's error rate and negatively affected the user experience

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