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۱Toward Application of Sandpile Model in Image Segmentation Based on Extremal Optimization Heuristic
اطلاعات انتشار: کنگره ملی مهندسی برق، کامپیوتر و فناوری اطلاعات، سال
تعداد صفحات: ۵
The sandpile model is a paradigm of self organizing critically (SOC) concept that is inspired by a physics–based intuition for optimization. In this paradigm, physical properties of sandpiles such as avalanche promise improved convergence and lower computations. Extremal Optimization (EO) algorithm is a general–purpose local search heuristic that is based on SOC. Here, application of sandpile model to image segmentation is proposed. In the proposed model, over–segmented images are submitted to the algorithm. Inspired by sandpile model, similar segments then merge, and by using the energy function in Markov random fields (MRF), EO adjusts the labels of pixels. Results indicate that sandpile model can be applicable to image segmentation<\div>

۲SEIMCHA: A New Semantic Image CAPTCHA Using Geometric Transformations
اطلاعات انتشار: International Journal of Information Security، چهارم،شماره۱، Jan ۲۰۱۲، سال
تعداد صفحات: ۱۴
As protection of web applications are getting more and more important every day, CAPTCHAs are facing booming attention both by users and designers. Nowadays, it is well accepted that using visual concepts enhance security and usability of CAPTCHAs. There exist few major different ideas for designing image CAPTCHAs. Some methods apply a set of modifications such as rotations to the original image saved in the data base, to make the CAPTCHA more secure. In this paper, two different approaches for designing image based CAPTCHAs are introduced. The first one–which is called Tagging image CAPTCHA–is based on pre–tagged images, using geometric transformations to increase security, and the second approach tries to enhance the first one by eliminating the use of tags and relying on semantic visual concepts. In fact, recognition of upright orientation is used as a visual cue. The usability of the proposed approaches is verified using human subjects. An estimation of security is also obtained by different kinds of attacks. Further studies are done on the proposed transformations and also on the properness of each original image for each approach. Results suggest a practical Semantic Image CAPTCHA which is usable and secure compared to its peers.
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