基于概念格的图像语义自动标注

【作者】 周亮亮；

【导师】 张继福； 张素兰；

【作者基本信息】 太原科技大学 ， 计算机软件与理论， 2012， 硕士

【摘要】 图像语义自动标注是当前图像领域的热点研究问题之一，基于BOV模型的图像表示是典型的图像语义自动标注方法之一，已得到广泛的应用。由于大多数基于BOV模型的图像语义标注关注的是如何提取更恰当视觉单词，忽略了视觉单词和图像语义之间的关系，因而图像语义标注效果较差。概念格是一种有效的数据分析工具，具有表示知识的直观性、完备性和概念的层次性等特点，在许多领域取得了较好的应用效果。本文采用概念格作为语义标注工具，对图像语义自动标注方法进行了研究，其主要研究成果为：1给出了一种使用概念格约简分析视觉单词的方法。首先用BOV图像表示方法，提取图像中的特征点并量化形成视觉单词；然后把图像标示作为形式背景对象集，图像对应的视觉单词作为形式背景属性集，视觉单词归一化（0-1归一化）结果作为对象和属性之间的关系形成形式背景，采用概念格属性约简的方法求取最小的属性集，以达到约简视觉单词，提高图像语义标注精度的目的；最后实例分析表明，该方法可以有效约简视觉单词。2给出了一种基于概念格的图像语义标注模型。利用约简后视觉单词作为形式背景，构造其相应的概念格，依据概念格节点外延数确定内涵的重要程度，进而确定视觉单词的重要程度，并使用这些视觉单词标注图像的语义。实验结果分析表明，该方法可以有效地进行图像语义自动标注。3）在上述研究的基础上，使用MATLAB、JAVA作为开发工具，设计与实现了基于概念格的图像语义标注原型系统，并采用Oliva和Torralba提出的图像库，实验验证了该系统实现图像语义自动标注是可行的、有价值的。更多还原

【Abstract】 Image semantic annotation is one of the most hot research issue in the fieldof image, and the BOV method is a typical image semantic annotation method，which has been applied widely. Most of the methods of image semanticannotation focus on how to extract more appropriate visual words, but ignore therelationship between the words and images. Concept lattice which is an effectivetool for data analysis, has the feature of intuition, completeness and concepthierarchy on knowledge representation, and has achieved good application effectin many fields. In the thesis, the method of image semantic automatic annotationis studied by using the concept lattice as semantic annotation tool. The mainresearch work is shown as follows:1A visual words reduction method is presented by using concept lattice asreduction tool. Firstly, feature points in images are extracted, and quantified intovisual words by using BOV image representation. Secondly, the visual words aretransformed into formal context among which images are used as object set,visual words as attribute set, and visual words are normalized as relationship ofobject and attribute. Thirdly the visual words are reduced through attributereduction to improve the precision of image semantic annotation. Instanceanalysis shows that the method can effectively simplify visual words.2A new model of image semantic annotation is presented based on conceptlattice. By using of the reduced form of concept lattice, the method firstlygenerates corresponding concept lattice structure. Then the important degree ofthe visual words is determined by the quantity of the extension. Finally thoseimportant words are used for image semantic annotation. Experimental resultsshow that the method can effectively carry out the image semantic annotation.3On the basis of the above research, the concept lattice based imagesemantic annotation prototype system is designed and implemented by usingMATLAB and JAVA as development tools, Oliva and Torralba ‘s image libraryas experimental data. The experiments show that the prototype system is feasibleand valuable.更多还原