空间隐喻视角下的“前”“后”认知

在日常汉语使用中,由"前""后"形成的几百个词条已经词汇化并具有了某种规约意义。为探究其意义形成过程,文章基于语料统计,从空间隐喻的角度对汉语中这一对高频词语作出认知解读,通过剖析二者的意象图式,重点从社会等级这一目标域分析"前""后"的隐喻意义拓展模式,并得出"地位较重要为前\地位较次要为后"的认知结论。文章还将顺应这一研究模式,运用语料统计、内省法等研究方法进一步对二者在其它目标域的隐喻意义拓展作出解析。     

基于纹理尺寸自适应的Criminisi图像修复改进算法

针对Criminisi图像修复算法中样本块选择的随意性,导致图像修复效果欠佳的缺陷,提出一种针对纹理图像的Criminisi改进算法。该算法通过对纹理图像预处理后获得的二值化图像进行统计分析,获得图像的行和列纹理曲线,进而得到纹理曲线的极值点变化曲线,并最终获得样本块的近似尺寸。仿真实验表明,将本文获取的样本尺寸作为Criminisi修复算法的样本尺寸,获得了较传统Cfiminisi算法更好的视觉效果。     

Detecting shifted double JPEG compression tampering utilizing both intra-block and inter-block correlations

Copy-paste forgery is a very common type of forgery in JPEG images.The tampered patch has always suffered from JPEG compression twice with inconsistent block segmentation.This phenomenon in JPEG image forgeries is called the shifted double JPEG(SDJPEG) compression.Detection of SDJPEG compressed image patches can make crucial contribution to detect and locate the tampered region.However,the existing SDJPEG compression tampering detection methods cannot achieve satisfactory results especially when the tampered region is small.In this paper,an effective SDJPEG compression tampering detection method utilizing both intra-block and inter-block correlations is proposed.Statistical artifacts are left by the SDJPEG compression among the magnitudes of JPEG quantized discrete cosine transform(DCT) coefficients.Firstly,difference 2D arrays,which describe the differences between the magnitudes of neighboring JPEG quantized DCT coefficients on the intrablock and inter-block,are used to enhance the SDJPEG compression artifacts.Then,the thresholding technique is used to deal with these difference 2D arrays for reducing computational cost.After that,co-occurrence matrix is used to model these difference 2D arrays so as to take advantage of second-order statistics.All elements of these co-occurrence matrices are served as features for SDJPEG compression tampering detection.Finally,support vector machine(SVM) classifier is employed to distinguish the SDJPEG compressed image patches from the single JPEG compressed image patches using the developed feature set.Experimental results demonstrate the efficiency of the proposed method.     

基于图像分析的粗集料三维形态指标研究

粗集料的三维形态特征对沥青混合料的路用性能有着重要影响.为了获取不同岩性、不同粒径粗集料的三维形状特征,利用粗集料形态特征研究系统,结合数字图像处理技术和数理统计方法,对不同岩性、不同粒径、多组粗集料进行了室内试验分析,方便准确地获取了集料的厚宽比和球度比的三维形态特征指标,并对石灰岩、花岗岩、玄武岩、安山岩、卵石,粒径分别为4.75 mm、9.5 mm、13.2 mm、16 mm、19 mm、26.5 mm的粗集料三维形态指标进行对比统计分析.试验结果表明:对于石灰岩、花岗岩、玄武岩、安山岩和卵石,当保证率为95％时,石灰岩的厚宽比最小,为0.290,其片状性较大,玄武岩的厚宽比最大,为0.366,其片状性较小.对于不同粒径的粗集料,花岗岩的厚宽比标准差最小,其变异性最小.花岗岩的球度随粒径变化最敏感,卵石的球度最接近1,即卵石的三维形状更接近球体.     

简易车辆类型识别系统设计

从实时视频数据流中检测出运动车辆并对其进行车辆类型识别是智能交通系统的重要组成部分。本文提出一种从AVI视频文件中检测出运动车辆并识别其车辆类型的方案,其系统处理过程分为车辆图像获取、图像处理和车辆外观特征数据提取三个主要部分。经实验验证,该设计简单可行。     

Application of Deep Learning Method on Ischemic Stroke Lesion Segmentation

Although deep learning methods have been widely applied in medical image lesion segmentation,it is still challenging to apply them for segmenting ischemic stroke lesions,which are different from brain tumors in lesion characteristics,segmentation difficulty,algorithm maturity,and segmentation accuracy.Three main stages are used to describe the manifestations of stroke.For acute ischemic stroke,the size of the lesions is similar to that of brain tumors,and the current deep learning methods have been able to achieve a high segmentation accuracy.For sub-acute and chronic ischemic stroke,the segmentation results of mainstream deep learning algorithms are still unsatisfactory as lesions in these stages are small and diffuse.By using three scientific search engines including CNKI,Web of Science and Google Scholar,this paper aims to comprehensively understand the state-of-the-art deep learning algorithms applied to segmenting ischemic stroke lesions.For the first time,this paper discusses the current situation,challenges,and development directions of deep learning algorithms applied to ischemic stroke lesion segmentation in different stages.In the future,a system that can directly identify different stroke stages and automatically select the suitable network architecture for the stroke lesion segmentation needs to be proposed.     

基于改进的 NCSPSO -AFSA 对 SVM参数的优化及其应用

为了找到支持向量机（SVM）最佳的分类参数,用以构建适合纹理图像分割的SVM分类器,文中是将基于小生境和交叉选择算子的粒子群算法（ NCSPSO）引入变异算子和族外竞争机制加以改进后与人工鱼群算法（ AFSA）混合,提出了一种改进的NCSPSO-AFSA混合算法优化支持向量机参数,并分别与AFSA算法,粒子群算法（PSO）,NCSPSO算法在图像分割准确率、参数寻优时间、图像分割时间等方面进行对比和分析,实验表明文中算法能够更好地获得适用于纹理图像分割的SVM参数,在缩短图像分割时间的同时提高了图像分割准确率,相比较其他算法,文中算法稳健性更好。将此方法应用于电镜及超声纹理图像分割中能较好地提取出目标区域,图像边缘部分的分类也很清晰。     

bcl-2蛋白和PCNA在乳癌中表达的定量测定及其预后

应用图像分析仪对６０例乳癌ｂｃｌ－２、ＰＣＮＡ和雌孕激素受体进行免疫组织化学及酶联亲和法定量研究。结果表明：ｂｃｌ－２蛋白定量高值组，乳癌组织学分级低，患者生存期长、生存率高（Ｐ＜０．０５）；ＰＣＮＡ表达定量高值组，组织学分级高，患者生存期短、生存率低（Ｐ＜０．０５）。显示了定量检测ｂｃｌ－２蛋白和ＰＣＮＡ对评估乳癌分化程度及判断预后具有一定价值。ｂｃｌ－２与雌孕激素受体间有显著的正相关性（Ｐ＜０．００１），提示ｂｃｌ－２蛋白检测对乳癌患者内分泌治疗有重要参考价值。     

水运交通电视监控图象传输技术研究

介绍水运交通电视监控图象通过电话线路的传输技术、相应的硬件装置、软件框图以及软件特点。特别是针对水运交通电视监控图象 ,对 JPEG编码标准作了修改 ,以进一步提高压缩比 ,以及自编调制解调器程序以充分发挥调制解调器的传输速率。最后介绍达到预期效果的系统性能测试及现场试验结果     

RT透照工艺技巧探讨

射线检测（RT）技术广泛用于船舶质量检验。根据CCS《钢质海船入级规范》（2006）及其修改通报的有关规定,在船舶的大接头,合拢缝,总焊缝等重要焊缝必须进行相当数量的射线拍照检查其焊缝的内部缺陷。通过该检测手段能较直观确定缺陷的性质以及缺陷的的位置和大小,弥补了超声波检测不直观,较难确定缺陷的缺点,成为重要和广泛应用的无损检测技术。本文着重阐述了RT透照过程中射线灵敏度、焦距、曝光量的控制以及暗室的处理技巧,为无损检测从业人员提高RT透照工艺水平提供参考。