انجمن کامپیوتر ایران

Accurate pupil segmentation is the first and most important step for an iris recognition system. Current methods are based on fitting a model such as circle or ellipse to find and detect pupil, while these methods don’t have sufficient accuracy and are sensitive to the specular spot reflection. In this paper, we utilize an optimized color mapping to increase the accuracy of pupil segmentation, regardless of pupil model and its shape (circular or elliptic), while removing the effects of specular spot reflection. The optimum color mapping can be established by an iterative minimization algorithm similar to Levenberg- Marquardt (LM) method. By applying this method, a new image is provided with a clear pupil region that can be easily segmented. Also a robust preprocessing step is presented in this paper that sharpens and clears pupil region. We obtain 98% accuracy in pupil boundary detection by applying this method on UBIRIS dataset. Also, the proposed method works well on any model of eye image even where the eye is not perpendicular to the camera.

In this paper, a fuzzy inference system by which reliability of features can be measured is designed. The reliability determines discriminative power of a feature in separating target from background. We focus our attention on design of membership functions. With a rational explanation on available information over a particle filter-base tracking process, we infer a coarse estimation of membership functions. It follows with a fine-tuning stage by using genetic algorithm. Color, edge, texture and TED are used in current work but the extension to a wider number of features is straightforward.

Particle Swarm Optimization (PSO) is an optimization method that is inspired by nature and is used frequently nowadays. In this paper we proposed a new dynamic geometric neighborhood based on Voronoi diagram in PSO. Voronoi diagram is a geometric naturalistic method to determine neighbors in a set of particles. It seems that in realistic swarm, particles take Voronoi neighbors into account. Also a comparison is made between the performance of some traditional methods for choosing neighbors and new dynamic geometric methods like Voronoi and dynamic Euclidean. In this comparison it is found that PSO with geometric neighborhood can achieve better accuracy overall especially when the optimum value is out of the initial range.

PEnT1 is an automatic English to Persian text translator. It translates simple English sentences into Persian, exploiting a combination of rule based and semantic approaches. It covers all the twelve tenses in English in both passive and active verbs for indicative, negative, interrogative sentences. In this paper, introducing PEnT1, we propose a new WSD method by presenting a hybrid measure to score different senses of a word. We also discuss prototyping some linguistic resources to test our methods.

The dynamic nature of service-oriented architecture (SOA), leads to a need for special attention about the turbulence of the quality attributes (or non-functional requirements) of software during the dynamic changes. If there exists a method for monitoring the whole quality of a service-oriented software, the service selector component of the architecture, which has the responsibility of choosing the best candidate service at runtime, can be aware of the quality state of the whole software at any moment of decision. In this paper, we have focused on the overall quality of an architecture which consists of multiple independent services and present a new method for tracing quality attributes in service oriented architecture based on Graph Transformation System (GTS) as a formal approach.