F. Yaghmaee; M. Kamyar
Abstract
To distinguish between human user and computer program to enhance security, a popular test called CAPTCHA is used on Web. CAPTCHA has an important role in preventing Denial Of Service (DOS) attacks in computer networks. There are many different types of CAPTCHA in different languages. Due to the expansion ...
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To distinguish between human user and computer program to enhance security, a popular test called CAPTCHA is used on Web. CAPTCHA has an important role in preventing Denial Of Service (DOS) attacks in computer networks. There are many different types of CAPTCHA in different languages. Due to the expansion of Persian-language and documents on internet, creating a suitable Persian CAPTCHA seems to be necessary. In this paper, we introduce three different types for Persian CAPTCHA in different domains. In the first type, based on the particular characteristics of Persian writing such as contiguous writing and image processing techniques, high strength CAPTCHA is provided. In the second type, the meaning of Persian words are used to creating CAPTCHA and in the third type, the combination of image processing techniques and the meaning of Persian words are used. Experimental results show that proposed CAPTCHAs has high security against attacks while Persian people can easily recognize them.
V. Maihami; F. Yaghmaee
Abstract
With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers ...
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With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper, we propose a novel image annotation algorithm based on neighbor voting which uses fuzzy system. The performance of the model depends on selecting the right neighbors and a fuzzy system with the right combination of features it offers.Experimental results on Corel5k and IAPR TC12 benchmark annotated datasets, demonstrate that using the proposed method leads to good performance.
