Image Fragment CAPTCHA for Bot-Proof Human Verification
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Solution Overview
Problem
Conventional text-based CAPTCHAs are becoming increasingly vulnerable to algorithmic systems due to advancements in character recognition, and they pose usability issues for diverse user groups, especially on mobile devices, leading to frustration and dissatisfaction.
Innovation Solution
A two-component system that segments images into radially symmetrical fragments, allowing users to rearrange and rotate them, making it difficult for algorithms to correctly align the fragments while remaining recognizable to humans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If text-based CAPTCHAs use higher complexity and distortion to prevent algorithmic recognition, then security against bots is improved, but usability for human users deteriorates
Solution Approach 1:
The patent divides an image into multiple fragments or tiles that are then scrambled and presented to the user. This segmentation approach allows the system to maintain security through complex rearrangement while preserving usability because users can mentally reconstruct the original image by assembling the fragments, whereas algorithmic systems struggle with the combinatorial complexity of correct assembly.
Solution Approach 2:
The patent transitions from traditional text-based CAPTCHAs to image-based CAPTCHAs, adding a spatial dimension to the challenge. Instead of relying on character distortion in one dimension, the system uses multi-dimensional spatial relationships and fragment assembly, creating a challenge that is easier for humans to solve through pattern recognition while remaining difficult for algorithms.
2Reliability
If text-based CAPTCHAs increase distortion and noise to improve security, then algorithmic recognition is hindered, but character recognition precision by users decreases
Solution Approach 1:
By segmenting images into fragments rather than distorting the entire image, the patent avoids degrading overall image quality and recognizability. Each fragment maintains sufficient visual information for users to identify its content, while the security challenge arises from the combinatorial complexity of assembling them correctly, not from loss of visual detail.
Solution Approach 2:
The patent uses copies or fragments of the original image rather than heavily distorting the original. These fragments are rearranged to create the CAPTCHA challenge, preserving the visual quality and recognizability of the image content while creating a new security challenge based on spatial arrangement rather than visual distortion.
3Adaptability or versatility
If CAPTCHA images are made smaller for mobile device display, then device compatibility is improved, but the level of detail and complexity for protection is reduced
Solution Approach 1:
The patent divides images into a manageable number of fragments suitable for mobile display sizes. This segmentation allows the CAPTCHA to maintain security through the assembly challenge while adapting to smaller screens, as the fragment-based approach scales better than high-resolution distorted text images would on mobile devices.
4Reliability
If multiple complex CAPTCHA tests are presented to ensure security, then protection reliability is improved, but user frustration and dissatisfaction increase
Solution Approach 1:
The patent presents a single image-based CAPTCHA challenge that inherently provides strong security through its fragment assembly mechanism. This eliminates the need to present multiple sequential CAPTCHAs, reducing user frustration while maintaining security. The segmentation approach creates a challenge that is sufficiently difficult for algorithms but intuitive for humans to solve in one attempt.
Data Source
AI summary
This invention is an image-based CAPTCHA system that relies on human users changing location and orientation of multiple partial fragments of complete images. The underlying source images represent objects, symbols, concepts or text recognizable by a human user. Such source images are fragmented by the system into a group of image fragments, with selected portions of resulting fragments being omitted and optionally distorted in order to prevent automated assembly of the resulting group of fragments into a representation of the source image by simple means of boundary inspection. Once the user arranges the fragment tiles into the orientation that they believe represents the original image and submits their answer to the system, the user's answer is evaluated to determine whether the challenge posed by the system was passed successfully.