Text-based CAPTCHAs remain a widely deployed mechanism to distinguish humans from automated bots. The Telerik RadCaptcha, a component of the ASP.NET AJAX suite, generates distorted alphanumeric images with character overlap, intersecting lines, and dynamic background noise. This study introduces a novel, real-world dataset of 3,000 labeled Telerik RadCaptcha images and proposes a specialized multi-stage preprocessing pipeline featuring adaptive binarization and contour-based segmentation to robustly isolate overlapping and noisy characters—challenges where conventional methods frequently fail. The segmented characters are then classified using a lightweight Convolutional Neural Network (CN... More >