Image segmentation towards new image representation methods

Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.     

Stability analysis and antiwindup design of uncertain discrete-time switched linear systems subject to actuator saturation

This paper investigates the stability analysis and antiwindup design problem for a class of discrete-time switched linear systems with time-varying norm-bounded uncertainties and saturating actuators by using the switched Lyapunov function approach.Supposing that a set of linear dynamic output controllers have been designed to stabilize the switched system without considering its input saturation,we design antiwindup compensation gains in order to enlarge the domain of attraction of the closed-loop system in the presence of saturation.Then,in terms of a sector condition,the antiwindup compensation gains which aim to maximize the estimation of domain of attraction of the closed-loop system are presented by solving a convex optimization problem with linear matrix inequality(LMI)constraints.A numerical example is given to demonstrate the effectiveness of the proposed design method.     

Convex relaxation for a 3D spatiotemporal segmentation model using the primal-dual method

A method based on 3D videos is proposed for multi-target segmentation and tracking with a moving viewing system. A spatiotemporal energy functional is built up to perform motion segmentation and estimation simultaneously. To overcome the limitation of the local minimum problem with the level set method, a convex relaxation method is applied to the 3D spatiotemporal segmentation model. The relaxed convex model is independent of the initial condition. A primal-dual algorithm is used to improve computational efficiency. Several indoor experiments show the validity of the proposed method.     

基于像素拓展的图形分割与合成的方法研究

提出了一种新的图像分割与合成方法。对于图像的分割,提出了新的分割算法,先是手工将一些明显属于物体和明显属于背景的像素分割出来,然后创建一个小矩形区域进行像素拓展迭代,迭代到图像边界为止。对于图像的合成,采用平均法,设计了新的算法,使物体的基本颜色保持不变的同时,降低了合成图像中从源图像分割的物体与新背景的差异,并使得其饱和度、色度、强度更加自然真实。     

根据客户网络应答的DNS服务器设计与实现

为了解决网络互连带宽"瓶颈"问题,很多单位的WWW服务器或邮件服务器同时申请不同网络的IP。若这些服务器所申请的不同网络IP对应不同的域名,即通过不同域名来区分不同的访问线路,会给用户访问服务器时带来不便。而一种能根据客户源IP地址所归属网络,把同一个域名解析成不同IP地址的DNS服务器的实现,既解决带宽"瓶颈"问题又方便网民。在Windows平台下,设计和实现了具有根据客户所归属网络应答功能的DNS服务器。     

模型驱动下的Web应用系统自动生成

为了提高Web应用系统开发效率,提出了模型驱动下的Web应用系统自动生成方法。这种生成方法是以Me—taEdit＋作为元建模工具,首先创建Web应用系统元模型、定制DSL,进而建立Web应用系统领域模型,然后通过MetaEdit＋提供的生成器定义语言MERL,软件开发人员可以很方便地设计出Web应用系统所需的JSP生成器、Servlet生成器、Jayabeans生成器和数据库生成器,从Web应用系统图形模型直接生成整个Web应用系统。最后通过一个WebShopping实例详细介绍了模型驱动下的Web应用系统生成方法及生成过程。经测试,所生成的Web应用系统可以在Windows操作系统中的Web应用服务器上正确运行。     

中医方剂与图集的转换方法

中药复方数据挖掘研究是将我国丰富的中药信息资源和现代最新信息技术相结合的重要内容,它意味着基于中医理论,利用知识发现技术,对传统中药新药、中医组方理论及规律、中药作用机制、有效成分构效关系等多个方面进行全面、系统的研究。图作为一种经典的数据结构,被广泛用于复杂数据结构分析与建模。文章探讨了图建模技术并实现了中医方剂与图集的转换。     

RAFNet: RGB-D attention feature fusion network for indoor semantic segmentation

Semantic segmentation based on the complementary information from RGB and depth images has recently gained great popularity, but due to the difference between RGB and depth maps, how to effectively use RGB-D information is still a problem. In this paper, we propose a novel RGB-D semantic segmentation network named RAFNet, which can selectively gather features from the RGB and depth information. Specifically, we construct an architecture with three parallel branches and propose several complementary attention modules. This structure enables a fusion branch and we add the Bi-directional Multi-step Propagation (BMP) strategy to it, which can not only retain the feature streams of the original RGB and depth branches but also fully utilize the feature flow of the fusion branch. There are three kinds of complementary attention modules that we have constructed. The RGB-D fusion module can effectively extract important features from the RGB and depth branch streams. The refinement module can reduce the loss of semantic information and the context aggregation module can help propagate and integrate information better. We train and evaluate our model on NYUDv2 and SUN-RGBD datasets, and prove that our model achieves state-of-the-art performances.     

Quadratic polynomial guided fuzzy C-means and dual attention mechanism for medical image segmentation

Medical image segmentation is the most complex and important task in the field of medical image processing and analysis, as it is linked to disease diagnosis accuracy. However, due to the medical image's high complexity and noise, segmentation performance is limited. We propose a novel quadratic polynomial guided fuzzy C-means and dual attention mechanism composite network model architecture to address the aforementioned issues (QPFC-DA). It has mechanisms for channel and spatial edge attention, which guide the content and edge segmentation branches, respectively. The bi-directional long short-term memory network was added after the two content segmentation branches to better integrate multi-scale features and prevent the loss of important features. Furthermore, the fuzzy C-means algorithm guided by the quadratic polynomial can better distinguish the image's weak edge regions and has a degree of noise resistance, resulting in a membership matrix with less ambiguity and a more reliable segmentation result. We also conducted comparison and ablation experiments on three medical data sets. The experimental results show that this method is superior to several other well-known methods.     

基于等级保护的网络改造方法及异常情况分析与处理

本文介绍了在电力企业信息网中基于等级保护的网络安全防护改造方法。在具体案例中,针对网络改造过程中遇到的网络异常情况,技术人员通过逐一分析、排查,最终恢复正常网络,达到企业信息网络二级域改造的目的。网络安全防护改造方法以及异常情况分析排查案例对同类型企业在网络改造及异常排查工作中具有一定借鉴和指导意义。