基于块内容和支持向量回归的图像质量客观评价模型

通过分析人眼对不同图像类型块的敏感度和支持向量回归（SVR）的特性，提出了一种基于块内容和SVR的图像质量评价模型。该模型首先根据图像子块的交流能量的关系，自适应地把图像分成边缘块、纹理块和平坦块3种类型；接着对不同类型块的失真程度采用图像块质量评价方法进行度量，得到图像各类型块的质量分数；其后利用SVR来学习3种类型块的质量分数与主观评价值的关系；最后用训练好的SVR完成图像质量预测。在实验过程中，图像各类型块失真程度评价采用了奇异值分解（SVD）方法、方向投影（DP）方法和投影能量（PE）方法。从实验结果可以得到，该模型克服了图像3种类型子块质量分数的权值讨论，从而使SVD方法、DP方法和PE方法的评价性能得到了有效提高，这表明该模型对图像块质量评价方法性能提高具有一定的普适性。

复杂零件金属注射成形3D充模模拟

以实际生产的支持块为例,结合3D技术,模拟了注射成形喂料在复杂几何模腔中的流动情况。基于ANSYS提供的Z Buffer切片模型空间观测方式,预测了实际制品缺陷产生的部位并分析了缺陷形成机理。最后依据模拟结果,推荐在实际生产中采用INLET4位置浇口进行注射生产,实验表明制得的支持块无缺陷,产品通过了有关部门的验收,证明了充模流动3D模拟的可行性和准确性。

Automatic detection and removal of static shadows

In case of complex textures,existing static shadow detection and removal algorithms are prone to false detection of the pixels.To solve this problem,a static shadow detection and removal algorithm based on support vector machine(SVM)and region sub-block matching is proposed.Firstly,the original image is segmented into several superpixels,and these superpixels are clustered using mean-shift clustering algorithm in the superpixel sets.Secondly,these features such as color,texture,brightness,intensity and similarity of each area are extracted.These features are used as input of SVM to obtain shadow binary images through training in non-operational state.Thirdly,soft matting is used to smooth the boundary of shadow binary graph.Finally,after finding the best matching sub-block for shadow sub-block in the illumination region based on regional covariance feature and spatial distance,the shadow weighted average factor is introduced to partially correct the sub-block,and the light recovery operator is used to partially light the sub-block.The experimental results show the number of false detection of the pixels is reduced.In addition,it can remove shadows effectively for the image with rich textures and uneven shadows and make a natural transition at the boundary between shadow and light.

The Design ＆ Implementation of Multimedia Sensor Node and the Building of Multimedia Network in Smart Home

With the requirements of multimedia service increasing in people＇ s life, sensor modules such as microphone, camera are added in the smart home＇ s sensor network, and the acquisition and processing of a large amount of information media such as audio, image and video is becoming a significant characteristics of smart home. The paper focuses on solving the following technical problems： the building of Zigbee multimedia network, the Design and selection of multimedia sensor node. These provide the basic network platform and the core technical support for the building of smart home.

Upper bound solution of supporting pressure for a shallow square tunnel based on the Hoek-Brown failure criterion

To analyze the stability of a shallow square tunnel, a new curved failure mechanism, representing the mechanical characteristics and collapsing form of this type of tunnel, is constructed. Based on the upper bound theorem of limit analysis and the Hoek-Brown nonlinear failure criterion, the supporting pressure derived from the virtual work rate equation is regarded as an objective function to achieve optimal calculation. By employing variational calculation to optimize the objective function, an upper bound solution for the supporting pressure and the collapsing block shape of a shallow square tunnel are obtained. To evaluate the validity of the failure mechanism proposed in this paper, the solutions computed by the curved failure mechanism are compared with the results calculated by the linear multiple blocks failure mechanism when the Hoek-Brown nonlinear failure criterion is converted into the Mohr-Coulomb linear criterion. The influences of rock mass parameters on the supporting pressure and collapsing block shape are discussed.