Security of authentication is needed to be provided superlatively to secure users personal and exchange information since online information exchange systems have been developed according to internet speed. Therefore, the aim of this paper is to develop existing graphical password scheme based on one's memory, create and implement a new graphical password scheme that composed of three layer verification. We programmed our scheme in order to prove its superiority comparing with existing schemes. While we conducted survey on user by accessing participant to our system lied in participants local network and we analyzed in accordance with the average length of their created password and statistical significant of entropy bit. From the survey results of total participants, we find that our scheme has statistical significant, furthermore it was proved that it can secure from a variety of attacks due to its high entropy.
Data visualization is a general term that describes any effort to help people enhance their understanding of data by placing it in a visual context. We present a ubiquitous pattern of knowledge evolution that the collective digital society is experiencing. It starts with a challenge or goal in the real world. When implementing a real-world solution, we often run into barriers. Creating a digital solution to an analogue problem create massive amounts of data. Visualization is a key technology to extract meaning from large data sets.
In computer graphics, ray tracing is very simple and powerful method to present physical phenomena especially light-related things such as reflection and refraction since it traces the ray from the eye to the light source; however, we cannot understand how the result image is generated. Then, this chapter describes the mechanism of reflection and refraction. It is very time-consuming to render the target object considering reflection and refraction. If the object distorted by reflection and refraction is previously obtained, it is very fast to generate the result image since all we have to do is to render the distorted object without considering reflection and refraction. In the proposed method, firstly, a virtual object, which is constructed with vertices translated from original ones by considering reflection and refraction, is generated. Then, the image with reflection and refraction is generated by rendering the virtual object. In the analysis, total reflection and attenuation of light power are also considered. At last, the proposed method is applied to two types of transparent objects: cubed glass and cylindrical glass, and the comparison between the simulation results and the real photos is performed to demonstrate that the generated images are the same as the real ones.
In the world of lighting engineering, one of the most active areas of research and industrial application is in the definition of the color rendering properties of light sources. There is a current international standard, and several new methods have been proposed over the last decade. Ordinary consumers are frequently left with little or no knowledge of how to interpret the numerical data produced by any of these systems. This situation has been exacerbated with the advent of LED light sources with widely differing properties. Certain LEDs yield very different results depending on the particular metric in use. We have designed a color graphical system that allows a user to pick a set of (typically) 16 surface color samples, and to be given a realistic comparison of the colors when illuminated by two different light sources, shown on a side-by-side display on a color monitor. This provides a visual analogy to the computations built into the above-mentioned metrics, all of which are based on comparison techniques. This chapter will provide an insight into the design and operation of our lighting computer graphics visualization system. Mention will also be made of similar systems that may be found in the published literature.
This survey paper provides an overview of topological visualisation techniques for scalar data sets. Topological algorithms are used to reduce scalar fields to a skeleton by mapping critical changes in the topology to the vertices of graph structures. These can be visualised using graph drawing techniques or used as a method of seeding meshes of distinct objects existing in the data. Many techniques are discussed in detail, beginning with a review of algorithms working on scalar fields defined with a single variable, and then generalised to multivariate and temporal data. The survey is completed with a discussion of methods of presenting data in higher dimensions.
In this paper we extend the work of (Louw and Nicolls, 2007) which proposed a novel Markov Random Field formulation for resolving sparse features correspondences in image pairs. The MRF terms can include cliques of variable sizes, and the energies are minimized using Loopy Belief Propagation. In this paper, an improved MRF topology is developed which uses a variant of the previously developed KN-means algorithm (where each mean has a specified number of neighbours). The message passing schedule is an accelerated one which converges faster than the usual parallel message update schedule, and surprisingly, often gives better correspondence results. The method is compared to other state of the art sparse feature correspondence algorithms and shown to compare well. Outliers are handled naturally within this paradigm.
For tracking head motions from a sequence of video images, segmentation of faces usually takes place first to locate head positions. Although a plethora of methods have been developed to segment faces, each approach has its own advantages and disadvantages depending on the properties of collected video clips, especially under low luminance level (i.e. lower than 10 cd/m 2) . This study extends a traditional approach based on skin colour to segment faces, and has arrived at a mixed-colour-space algorithm, which takes viewing illumination and post position into consideration and shows very promising segmentation results with fewer false regions. The procedure includes obtaining colour attributes that are selected from varying colour spaces/models in order to detect the regions of interest (ROIs), which maximises the characteristics of faces. Colour edges are then applied to classify ROI into faces.
Todays vehicles are more and more equipped with video cameras. These cameras are used e.g. for lane and parking assist systems. For the localization of the vehicle in the world the Global Positioning System is widely used. Unfortunately, GPS is very imprecise and insufficient for many driver assistance applications. To overcome this limitation, a more precise localization using a differ ent approach has to be found. High quality localization sensors are already available on the market but still too expensive for mass integration in automobiles. The aim is to extract additional information from already established car equipment and to use it for precise localization. Our approach combines map information with extracted image features using a model based algorithm.
