Abstract: Websites can enhance their security and protect against malicious Internet attacks by implementing CAPTCHA verification to distinguish between human users and automated bots. Text-based CAPTCHAs are commonly used as they are easy for humans to solve but challenging for machines to decipher. This research introduces a CNN model that utilizes binary images to recognize CAPTCHAs efficiently. The project involves creating an advanced Captcha Recognition System using deep learning on a Raspberry Pi. In real-time, the Raspberry Pi processes images with the help of OpenCV, applying the trained model to authenticate captchas. This innovative approach demonstrates the practical use of deep learning on edge devices, strengthening security through automated captcha verification and showcasing the potential for IoT security solutions in real-world applications.
Key terms: Convolutional neural network; OpenCV; Automated CAPTCHA verification.
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DOI:
10.17148/IJARCCE.2024.13472
