Persian/Arabic Baffletext CAPTCHA

Nowadays, many daily human activities such as education, trade, talks, etc are done by using the Internet. In such things as registration on Internet web sites, hackers write programs to make automatic false registration that waste the resources of the web sites while it may also stop it from functioning. Therefore, human users should be distinguished from computer programs. To this end, this paper presents a method for distinction of Persian and Arabic-language users from computer programs based on Persian and Arabic texts. Our proposed algorithm is based on adding a background to the image of a meaningless Persian/Arabic randomly generated word. This method relies on the difficulty of automatic separation of background from Persian/Arabic writing, due to the presence of many diacritical dots and signs. In this method, the image of a random meaningless Persian or Arabic word is shown to the user and he is asked to type it. Considering that the presently available Persian and Arabic OCR programs cannot identify these words, the word can be identified only by a Persian or Arabic- language user. This method also can be used to prevent program attacks, resource waste and performance reduction. The proposed method has been implemented by the Java language. The generated words are tested, using ReadIris and Omnipage OCR systems. These OCR systems were unable to recognize these words.

[1]  Henry S. Baird,et al.  BaffleText: a Human Interactive Proof , 2003, IS&T/SPIE Electronic Imaging.

[2]  Venu Govindaraju,et al.  Handwritten CAPTCHA: using the difference in the abilities of humans and machines in reading handwritten words , 2004, Ninth International Workshop on Frontiers in Handwriting Recognition.

[3]  Jitendra Malik,et al.  Recognizing objects in adversarial clutter: breaking a visual CAPTCHA , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[4]  Wen-Hung Liao,et al.  Embedding information within dynamic visual patterns , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[5]  Henry S. Baird,et al.  ScatterType: a reading CAPTCHA resistant to segmentation attack , 2005, IS&T/SPIE Electronic Imaging.

[6]  Henry S. Baird,et al.  Pessimal print: a reverse Turing test , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[7]  Henry S. Baird,et al.  Implicit CAPTCHAs , 2005, DRR.

[8]  Kris Popat,et al.  Human Interactive Proofs and Document Image Analysis , 2002, Document Analysis Systems.

[9]  Tsz-Yan Chan,et al.  Using a test-to-speech synthesizer to generate a reverse Turing test , 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

[10]  Gabriel Moy,et al.  Distortion estimation techniques in solving visual CAPTCHAs , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..