A new image-based CAPTCHA using the orientation of the polygonally cropped sub-images

作者：Kim Jong Woo; Chung Woo Keun; Cho Hwan Gue^*

来源：Visual Computer, 2010, 26(6-8): 1135-1143.

DOI：10.1007/s00371-010-0469-3

• Image orientation
• CAPTCHA
• Machine learning
• Perceptual recognition

With an increasing number of automated software bots and automated scripts that exploit public web services, the user is commonly required to solve a Turing test problem, namely a Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), before they are allowed to use web services. As a solution of CAPTCHAs, the Image Orientation CAPTCHA is based on the hardness of image orientation. So, there is a close correlation between image orientation detection and the performance of image orientation CAPTCHA. In this paper, we introduce a reliable and effective CAPTCHA based on the orientation of cropped sub-images. Also, we try to investigate the key spatial features of sub-image orientation detection such as crop size, major color components, and the number of orientations. So, the goal of this paper is discovering the relationship between these spatial features and the detecting sub-image orientation by human manual work and machine learning-based softwares, respectively. Our experimental results enable our CAPTCHA system to filter out any sub-images difficult for human. Therefore, our experiment showed that exploiting the key spatial features of cropped sub-images is very useful to design a new image-based CAPTCHA system.

• 出版日期2010-6