Pure spatial rich model features for digital image steganalysis

The SRM (Spatial Rich Model) is a very effective steganalysis method. It uses statistics of neighboring noise residual samples as features to capture the dependency changes caused by embedding. Because the noise residuals are the high-frequency components of image and closely tied to image content, the residuals of different types of image regions have different statistical properties and effectiveness for steganalysis. In this paper, the effectiveness of the residuals is investigated. Then the effectiveness of the statistics collected from different types of neighboring residual samples is investigated from the FLD (Fisher Linear Discriminant) viewpoint, and ineffective, effective and high-effective neighboring residual samples are defined. The ineffective neighboring residual samples are not likely to change during embedding, and if they are counted in statistics, they may mix the features with noise and make the features impure. Pure SRM features are extracted based on neighboring noise residual sample selection strategy. Furthermore, multi-order statistical features are proposed to increase the statistical diversity. Steganalysis performances of the statistical features collected from different types of neighboring residual samples are investigated on three content adaptive steganographic algorithms. Experimental results demonstrate that the proposed method can achieve a more accurate detection than SRM.     

Secure three-party computational protocols for triangle area

In this work, we have put forth two different protocols to address a concrete secure multi-party computational (MPC) problem related to a triangle, of which the coordinates of the three vertices are confidentially kept by the three participants, respectively. The three parties wish to collaboratively compute the area of this triangle while preserving their own coordinate privacy. As one of the merits, our protocols employ weaker assumptions of the existence of pseudorandom generators. In particular, unlike massive secure MPC protocols that rely a lot on oblivious transfer, ours utilize a new computing idea called “pseudorandom-then-rounding” method to avoid this burdensome obstacle. The two protocols are based on different theorems, while they both make use of the same underlying idea. At last, we provide a detailed proof for the first protocol by a series of security reductions of our newly defined games, which seems somewhat stronger than the previous simulation-based proofs and a proof sketch for the second one. Analysis and discussion about the reasons are provided as well to round off our work.     

应用MES技术优化分组加工工艺过程

分组加工模式的应用是特色工艺研究和精细化加工的结合,目前被应用在了很多企业中。为了解决计划制订到生产调度指挥这一过程中的问题,企业采用了MES技术来优化这一模式下的工艺过程。分析了MES技术的应用。     

现代商业区建筑供配电设计要点及对策初论

在经济的推动下,商业区数量日益增多,空间布局更加紧凑,用电量也随之大幅增加,管理更为困难。因此,要重视商业区建筑的供电配电。介绍了商业区建筑的特点,然后结合实际案例对其供配电进行了设计。     

A high performance parallel DCT with OpenCL on heterogeneous computing environment

A noteworthy thing in desktop PCs is that they can provide a great opportunity to increase the performance of processing multimedia data by exploiting task- and data-parallelism with multi-core CPU and many-core GPU. This paper presents a high performance parallel implementation of 2D DCT on this heterogeneous computing environment. For this purpose, Intel TBB (threading building blocks) and OpenCL (Open Compute Language) are utilized for task- and data-parallelism, respectively. The simulation result shows that the parallel DCT implementations far the serial ones in processing speed. Especially, OpenCL implementation shows a linear speedup, a typical SIMD characteristic as the increase of 2D data sets.     

基于机器视觉的微片状物厚度检测

针对片状颗粒厚度检测的实际需求,结合机器视觉、图像处理和嵌入式技术,设计与实现了一套基于高性能ARM11的微片状颗粒厚度检测系统。该系统以QT和S3C6410为软硬件平台,提出了利用轮廓提取和最小矩形边界框相结合的方法计算片状颗粒厚度。结果表明,该检测系统具有处理速度快,测量精度高和成本低廉等优点,满足了对颗粒厚度测量的需求。     

Image mosaicking for polyhedral scene and in particular singly visible surfaces

Image mosaic construction is about stitching together a number of images about the same scene to construct a single image with a larger field of view. The majority of the previous work was rooted at the use of a single image-to-image mapping termed planar homography for representing the imaged scene. However, the mapping is applicable only to cases where the imaged scene is either a single planar surface, or very distant from the cameras, or imaged under a pure rotation of the camera, and that greatly limits the range of applications of the mosaicking methods. This paper presents a novel mosaicking solution for scenes that are polyhedral (thus consisting of multiple surfaces) and that are pictured possibly in closed range of the camera. The solution has two major advantages. First, it requires only a few correspondences over the entire scene, not correspondences over every surface patch in it to work. Second, it conquers a seemingly impossible task—warping image data of surfaces that are visible in only one of the input images, which we refer to as the singly visible surfaces, to another viewpoint to constitute the mosaic there. We also provide a detail analysis of what determines whether a singly visible surface could be mosaicked or not. Experimental results on real image data are presented to illustrate the performance of the method.