Deep Learning Analysis of Amodal Completion CAPTCHA with Colors and Hidden Positions
Tomoka Azakami, Ryuya Uda · 2017
Existing CAPTCHA methods are able to be read by computers owing to the development of technologies. We proposed a CAPTCHA method with amodal Completion in order to prevent computers from reading CAPTCHA. We also applied aftereffects and colors for the method to enhance visibility. However, our method was completely able to be read by computers with deep learning. However, we were able to discover the undetermined element and problems in our research and the research was not a waste since we found problems and some hits to improve our method. This study was conducted to expect that we get the opportunity to create a more robust CAPTCHA by improving them.