Uses Canny edge detection and OpenCV to locate puzzle pieces in slide-based CAPTCHAs for automated solving.
slide_captcha_cracker is an open-source Python tool that locates puzzle pieces in slide-based CAPTCHA images using Canny edge detection and OpenCV. It solves the specific problem of determining where a puzzle fragment belongs in a background image, which is a key step in automating CAPTCHA challenges.
Security researchers, QA testers, and developers working on automation scripts or studying CAPTCHA vulnerabilities who need a simple, educational example of image-based localization.
It provides a clear, minimal implementation focused solely on the localization step using standard OpenCV functions, making it easy to understand, modify, and integrate into larger projects compared to more complex, black-box solutions.
Canny算子边缘检测识别滑动验证码
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Provides a minimal, OpenCV-based implementation using Canny edge detection and contour extraction, making it easy to understand slide CAPTCHA localization from the code and online demo.
Specifically targets the puzzle localization step, as noted in the README, allowing seamless integration into broader CAPTCHA-solving pipelines without bloat.
Includes an online demo and screenshot, enabling users to test the functionality directly and see the edge detection and matching process in action.
Uses well-known OpenCV functions like GaussianBlur and cross-correlation, reducing the learning curve for developers familiar with basic computer vision.
Only handles localization; the README explicitly states that encryption, data obfuscation, and behavior simulation are separate, unaddressed challenges for real-world CAPTCHAs.
Designed for basic slide CAPTCHAs without defenses, making it ineffective against modern variants with dynamic puzzles or anti-bot measures mentioned in the '其他' section.
The README is brief and primarily in Chinese, with sparse details on setup, parameter tuning, or error handling, hindering accessibility for non-Chinese speakers.