A survey of occlusion detection method for visual object

Occlusion problem is one of the challenging issues in vision field for a long time , and the occlu-sion phenomenon of visual object will be involved in many vision research fields .Once the occlusion occurs in a visual system , it will affect the effects of object recognition , tracking, observation and operation , so detecting occlusion autonomously should be one of the abilities for an intelligent vision system .The research on occlusion detection method for visual object has increasingly attracted atten-tions of scholars .First, the definition and classification of the occlusion problem are presented . Then, the characteristics and deficiencies of the occlusion detection methods based on the intensity image and the depth image are analyzed respectively , and the existing occlusion detection methods are compared.Finally, the problems of existing occlusion detection methods and possible research directions are pointed out .     

基于改进Sobel算法的焊缝X射线图像气孔识别方法

提出一种具有自适应能力的焊缝X射线图像气孔检测方法.通过局部动态阈值分割法设计了多方向的焊缝X射线图像模板,采用Sobel算法对复杂背景下的焊缝进行边缘检测和区域标记,并在标记区域对原始图像x和y方向的灰度梯度进行分析,以增强小气孔和粘连气孔的识别能力.检测应用效果表明,所提出的方法具有良好的自适应能力且准确快速,能够有效地克服人工评片中产生的漏判与误判等缺点,并且能够存储和查询检测数据.     

Semantic image annotation based on GMM and random walk model

Automatic image annotation has been an active topic of research in computer vision and patternrecognition for decades.A two stage automatic image annotation method based on Gaussian mixturemodel (GMM) and random walk model (abbreviated as GMM-RW) is presented.To start with,GMM fitted by the rival penalized expectation maximization (RPEM) algorithm is employed to estimatethe posterior probabilities of each annotation keyword.Subsequently, a random walk processover the constructed label similarity graph is implemented to further mine the potential correlations ofthe candidate annotations so as to capture the refining results, which plays a crucial role in semanticbased image retrieval.The contributions exhibited in this work are multifold.First, GMM is exploitedto capture the initial semantic annotations, especially the RPEM algorithm is utilized to train themodel that can determine the number of components in GMM automatically.Second, a label similaritygraph is constructed by a weighted linear combination of label similarity and visual similarity ofimages associated with the corresponding labels, which is able to avoid the phenomena of polysemyand synonym efficiently during the image annotation process.Third, the random walk is implementedover the constructed label graph to further refine the candidate set of annotations generated byGMM.Conducted experiments on the standard Corel5k demonstrate that GMM-RW is significantlymore effective than several state-of-the-arts regarding their effectiveness and efficiency in the task of automatic image annotation.     

基于SIFT检测的Demons图像配准

提出一种计算简便且配准效率高的算法.通过拟牛顿对Demons算法里的目标函数进行优化,从而得出形变向量u的方法,阐明了此方法配准的高效性,同时再结合SIFT算法对配准结果的检测,便能很直接很直观地看出配准结果的好坏,避免了判断两幅图相似性的大量计算.实验验证了所提出算法的有效性.     

诗词意境研究中的若干问题

意境的现代性研究中衍生出了许多值得进一步探讨的问题,如意境的形象性问题,意境与意象的关系,意境的美学性质等等。意境是特种艺术形象,是由语象、意象依某种美学规则建构而成的三维空间形象,是实境和虚境的结合体,并以虚境的存在显示其独特的美学地位与价值。     

美育在医学院校学生素质教育中的作用探析

分析了当前影响医学院校学生审关能力的主要因素，探讨了美育在素质教育中的功能。从如何把美育融入校园文化建设等几个方面，提出了实施美育的措施。通过美育的正确实施，使学生以正确的审美价值观来支配自己的情感、意识和行为，以高雅的审美修养、审美情趣来完善自己的认识、情操和人格，催化综合素质的提高。     

古代文学中的“眉”意象探究

"眉"是中国古代关于美的一个象征,在历史发展的长河中,作为一种意象已经被沉淀为固有的民族文化内涵,也逐渐被人们接纳成为共同的意蕴。"眉"意象作为单象意象,虽然只是一个词汇,在古代文学作品中却包含了作者丰富的情感意蕴、审美情结和文化内涵,取得了别样的效果。     

基于核心元数据的海量影像编目数据查询

影像数据的查询是影像数据的发布与共享的前提，该文在对比研究围内外元数据制定与管理特点之后，针埘影像数据海量性特点，结合影像编目数据查询特点，提出基于核心元数据的海量影像编目数据查询方法，经过实验能够高效的实现海量影像编目数据的查询。     

一种基于样本块的图像超分辨率方法研究

提出了一种在马尔科夫网络框架下基于样本块的图像超分辨率算法。算法根据相似性选取多个样本块作为图像重建的候选,在候选集中计算图像块先验概率和图像块之间的相容性,最后在马尔科夫框架下选取最优图像块,合成最终的高分辨率图像。实验证明本文提出的算法具有较好的超分辨率效果。     

基于神经网络技术自动筛选Monastrol抑制剂的算法研究

带自动荧光显微镜的HCS（high content screening）系统是一种新兴的显微摄影、筛选和处理系统.HCS系统在摄影过程中会产生大量数据,人工筛选和识别费时费力.本文为了进行Monastrol抑制剂的筛选,基于前馈式神经网络技术研究了一种对HCS系统摄影的大量细胞同时进行特征提取和细胞显型识别的自动算法.在得到各个通道分离的图像后,对不同通道图像进行并行预处理,并采用神经网络和逻辑运算相结合的算法进行处理.我们将该方法运用于Monastrol抑制剂的筛选中,并将结果与人工识别结果进行分析比较.相比较前人提出的multi-phenotypic mitotic analysis（MMA）算法自动识别的正确率得以提高,可更好评估抗癌药剂效用.