Image-Based CAPTCHA Recognition Using Deep Learning Models
Huthaifa Mohammed Kanoosh, Ammar Farooq Abbas, Noora Nazar, Zainab Mejeed Khadim, Duaa A. Majeed, Sameer Saadoon Algburi · 2024
This study dives into the efficacy of deep learning models within the field of CAPTCHA recognition, with a primary focus on bolstering online security measures. Our inquiry suggests a unique perspective by using Convolutional Neural Networks (CNNs) to recognize and categorize CAPTCHA images appropriately. The procedural methodology comprises preprocessing these images and training CNN models to partition them into discrete groups. Through thorough experimentation and assessment, our proposed methodology exposes promising outcomes, as notably shown by our CNN Model 4 obtaining an amazing accuracy rate of 96%. These results demonstrate the usefulness of deep learning algorithms in the field of CAPTCHA detection. while stressing their crucial function in decreasing cybersecurity concerns. This study adds greatly to the development of CAPTCHA recognition systems. highlighting the criticality of deploying deep learning models to enhance internet security procedures.