Advanced Materials Research Vol. 717

Abstract: Real-time and seamless visualization of the Earth terrain based on Global Discrete Grids is a subject of considerable current attention. In this paper a multi-scales visualization model of the global terrain based on DQG (Degenerate Quadtree Grid) is approached. Our approach starts with a partition method, called Degenerate Quadtree Grid (DQG) and an encoding scheme of the corresponding grids is introduced briefly. Next, a multiple level of detail model related to viewpoint is presented. In this model, a criterion of terrain model simplification based on viewpoint and roughness of the degenerate quadtree node is developed. Then, making full use of the characteristics of quadtree structure, the cracks within quadtree blocks are induced by simplification. Thus, the cracks splicing are all seamless. In the end, the experiment and analysis are made with the global terrain data, GTOPO30. The results illustrate that: (1) the global terrain based on the DQG is seamless, hierarchical, and regular over the whole Earth; (2) the quantity of global DEM data can be reduced significantly; (3) the visual effect of the global multi-scale terrain is seamless by the model simplification ensuring the accuracy and efficiency of the terrain display.

Abstract: This paper addresses the issue of the quincunx patterned green channel interpolation method that is obtained by single sensor cameras. Our goal is to reconstruct the green channel in Bayer color filter array (CFA) data. We present a new filter-based method for the reduction of image artifacts in green channel. To reconstruct green channel, we trained a filter using least squares method. Experimental results confirm the effectiveness of the proposed method. Compared to other bilinear and bicubic filters, the improvement in quality has been achieved.

Abstract: Generally, a digital camera employs a single CCD or CMOS sensor. In a color imaging device, the color information is usually obtained in sub-sampled patterns of red, green and blue pixels. Thus, full-resolution color is afterward created from this sub-sampled CFA image. This process is normally called as demosaicking. In this paper, we analyze performance of Yamanaka patterned CFA in terms of CPSNR and S-CIELAB. We show the simulation results on test images.

Abstract: This paper introduced a problem of the modified Bayer pattern color filter array (CFA). A demosaicking method is also known as color interpolation, which is a digital camera process employed to restore a full-color imagery from an image with missing color information. In general, a CFA pair contains two green pixels and one red and blue pixel (RGGB). However, there exist alternatives such as RRGB or RGBB. In this paper, we study the effect of three different color arrays. Simulation results show that the obtained filters give good performance.

Abstract: Signal image halftoning approach quantizes each pixel to one bit binary pixel. During the process of error diffusion, the quantization difference at each pixel is fed back to the input to diffuse the quantization difference among the adjacent color or gray-level pixels. This paper proposes a new kernel for error diffusion to enhance halftoning quality by minimizing average error after the process. Simulation results section confirms that the obtained color and green channel result images are satisfactory.

Abstract: A Constrained Local Models is face tracking method based on variation of shape in the Allowable Shape Domain. The CLMs perform optimize strategy in patch. It has problem because occlusion and background. In this paper, variation of shape is constrained for solving this problem.The generating of shape allows only shape adjusted translation, rotation, scale. The proposed method prevent that the shape generate to abnormal forms. As a result, the alignment error is about 4.2 pixels in environment has complex background. Also, when part of the face occluded, the alignment error is about 18.1pixels.

Abstract: In this paper, we used eye tracking technology to investigate the cognitive mechanisms during peoples reading of narratives and statistical information, and our main study included two aspects: first, we explored the differences in behavior of people during their reading of different text information from the cognitive behavior view; second, we used the method of pattern recognition to classify the eye movement data which reflects the human thinking mode. We found different reading modes in different texts.

Abstract: SURF (Speeded Up Robust Features) is known to be a famous and strong but computationally still expensive.It has not attained real-time performance yet. In this paper we analysis the SURF in orientation and descriptors extraction method forresolvingsome problems. For example, matching images through the SURF algorithm spends too much time and causes some errors by integral images. We propose a novel orientation and descriptor algorithm to improve the conventional SURF. Theproposed method shows some advantages such as a faster speed.

Abstract: In this paper, we propose a simple noise assessment approach for sensors. We assume the input signal is contaminated by white additive and zero mean Gaussian noise which. To measure the noise level, we the intensity-homogeneous blocks are found first, and then we evaluate the noise variance in the blocks. To determined intensity-homogeneous blocks, we use high pass filter. Experimental results show that the presented method provides good performance for natural and artificial images over a large range of noise levels.

Abstract: In this paper, we propose a neural network-based algorithm for grouping machine and parts in cellular manufacturing. For grouping machines, we develop similarity coefficients which take into account both similarity and dissimilarity between machines. The machine cells are formed by an algorithm which is based on the maximum neural network. Another algorithm is used to find the part families associated with each machine cell. When compared with an existing algorithm, our algorithm shows better performance in terms of grouping efficiency and grouping efficacy.