Regional Noise Generation for CAPTCHA Crack-Proof Capability
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Solution Overview
Problem
Existing CAPTCHA image generation methods are vulnerable to machine recognition due to the ease with which noise points can be filtered out using median filtering and expansion algorithms, resulting in a high risk of being cracked by machines and poor crack-proof capability.
Innovation Solution
A CAPTCHA image generation method that involves selecting a first region with the CAPTCHA code and generating first noise points on it, while also generating second noise points in a separate region outside the first region, making it difficult for machines to filter out noise points using simple algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If noise points are generated on the whole CAPTCHA image or on the CAPTCHA code, then the crack-proof capability is improved, but the noise points can be easily filtered out by median filtering or expansion algorithms
Solution Approach 1:
The patent applies local quality by generating noise points with different characteristics in different regions of the image. Specifically, noise points generated on the CAPTCHA code region have different properties (such as density, size, or distribution patterns) compared to noise points generated in the background region. This regional differentiation makes it difficult for machines to apply a single filtering algorithm effectively, as the noise characteristics vary across different areas of the image.
2Ease of manufacture
If simple noise scrambling is performed on the initial image, then the generation process is simple and fast, but the generated CAPTCHA image has high risk of being cracked by machines
Solution Approach 1:
The patent segments the image processing into distinct regional operations. It divides the image into at least two regions: a first region containing the CAPTCHA code and a second region containing the background. Different noise generation strategies are applied to each region independently, allowing the system to maintain computational efficiency while significantly improving crack-proof capability through region-specific noise characteristics.
Data Source
AI summary
The present disclosure discloses a CAPTCHA image generation method and apparatus, and a server, relating to the field of computer technologies. According to the present disclosure, first noise points are generated on a CAPTCHA code in some regions of an initial image and second noise points are generated on a background of the image in another region, so that a machine cannot filter out the noise points in a CAPTCHA image by means of some simple algorithms, increasing difficulty in recognizing the CAPTCHA code by the machine, reducing a risk that the CAPTCHA code is cracked by the machine, and having a strong crack-proof capability.