New Method for Optimization of License Plate Recognition system with Use of Edge Detection and Connected Component

License Plate recognition plays an important role on the traffic monitoring and parking management systems. In this paper, a fast and real time method has been proposed which has an appropriate application to find tilt and poor quality plates. In the proposed method, at the beginning, the image is converted into binary mode using adaptive threshold. Then, by using some edge detection and morphology operations, plate number location has been specified. Finally, if the plat has tilt, its tilt is removed away. This method has been tested on another paper data set that has different images of the background, considering distance, and angel of view so that the correct extraction rate of plate reached at 98.66%.Comment: 3rd IEEE International Conference on Computer and Knowledge Engineering (ICCKE 2013), October 31 & November 1, 2013, Ferdowsi Universit Mashha

Privacy Games: Optimal User-Centric Data Obfuscation

In this paper, we design user-centric obfuscation mechanisms that impose the minimum utility loss for guaranteeing user's privacy. We optimize utility subject to a joint guarantee of differential privacy (indistinguishability) and distortion privacy (inference error). This double shield of protection limits the information leakage through obfuscation mechanism as well as the posterior inference. We show that the privacy achieved through joint differential-distortion mechanisms against optimal attacks is as large as the maximum privacy that can be achieved by either of these mechanisms separately. Their utility cost is also not larger than what either of the differential or distortion mechanisms imposes. We model the optimization problem as a leader-follower game between the designer of obfuscation mechanism and the potential adversary, and design adaptive mechanisms that anticipate and protect against optimal inference algorithms. Thus, the obfuscation mechanism is optimal against any inference algorithm

Patterns of uptake and repair following recasts and prompts in an EFL context: Does feedback explicitness play a role?

This study sought to examine the effectiveness of two categories of feedback, namely recasts and prompts. Also, the study focused on the relationship between subsets of each feedback type and the extent to which they led to learner uptake and repair in an EFL context. Data were collected through non-participant observations of three intact upper-intermediate EFL classes where 36 hours of interactions among 59 students and three teachers were audiotaped, transcribed, and analyzed in terms of pre-specified coding systems that addressed four different subtypes of prompts – clarification requests, repetitions, elicitations, and metalinguistic clues – and two recast subtypes – explicit and implicit recasts. Data analysis showed that among prompts, clarification requests led to the highest percentage of uptake whereas elicitations were associated with the highest repair percentage. As for recasts, more explicit ones led to higher percentages of uptake and repair. The results of the study may contribute to a more in-depth understanding of the patterns of uptake and repair in an EFL context. The study confirms the role of feedback explicitness in such a context