按例和按绘的图像检索研究模式识别与智能系统专业论文.docxVIP

摘要图像作为查询示例在系统数据库中进行检索。实验结果表明，本文方法不但对 摘要 图像作为查询示例在系统数据库中进行检索。实验结果表明，本文方法不但对 用户需求的语义对象有较好的检索效果，具有较好的查准率和查全率，而且还 能较准确地在结果图像中框选出用户感兴趣的语义对象。 关键词：基于内容图像检索 图像分割语义对象提取 规范化形状按例查 询按绘查询 AbstractABSTRACT Abstract ABSTRACT As the development of multimedia information technology and Intemet technology，image database is getting larger and larger．How to find a special image of interest from the mass database efficiently and effeetively has become a major issue to be solved．In this case，the research on content．based image retrieval was developed，and became a hot spot in the fields of multimedia information processing． The most existing systems of CBIR fulfill the tasks of retrieving the similar images through computing the degree of similarity of different images．Though those methods have achieved some Success，the retrieval results through most ex isting meth．ods are still not satisfactory．The main difficulty is that，the qualities of retrieval results by computers are much dependent on the features of images，and they have great differences with human beings who predict the degree of similarity of images through the image semantics．So，how to automatically acquire image semantics which meets the needs of users is the key to solving the problem of i mage／video retrieval． To solve this problem，this dissertation focuses on the research of image semantics extraction and user semantics acquisition．The main content and contribution are summarized as below： Firstly，this dissertation introduces the study background and significance of image／video retrieval，and provides a survey of the most important issues in the current literature in image and video indexing and retrieval． Subsequently,a novel semantic object extraction method——husking algorithm is presented in this dissertation．Firstly a Luv color histogram of image based method is used to estimate the color bandwidth，and then a mean shift algorithm with adaptive color bandwidth is employed to segment the inputted image．Finally，a husking al