Efficient Content-Based Image Retrieval

高效的基于内容的图像检索

• 批准号: 9711771
• 负责人: Linda Shapiro
• 金额: $ 24.7万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-15 至 2001-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9711771&HistoricalAwards=false
• 关键词: Efficient; Content; Based; Image; Retrieval

The goal of this research project is to design and implement a system for content-based image retrieval that can (1) provide a large variety of image-distance measures that can be used singly or in combination to satisfy a wide range of user needs and (2) provide rapid access to images, even in an extremely large database. The focus of the work is the development of a general, scalable architecture to support fast querying of very large image databases with user-specified distance measures. This includes the development of distance-measure-independent algorithms and data structures for efficient image retrieval from large databases. Methods for merging the general, distance-measure-independent algorithms with other useful techniques that may be distance measure specific, such as keyword retrieval and relational indexing, are being pursued. The problem of providing users with multiple distance measures of many different varieties is being studied. New methods for combining distance measures and a language in which users can specify their queries without detailed knowledge of the underlying metrics are being designed. A prototype system is being implemented to test the developed methods, and evaluation is being performed on both a large general image database and a smaller controlled database. The results of this research will be: (1) techniques that facilitate rapid retrieval of images by eliminating huge portions of the image database from the search, making content-based retrieval feasible on very large and growing databases; (2) new, high-level methods by which users can combine distance measures to form meaningful queries, so that content-based queries can become a standard way to query image databases; and (3) a general framework for content-based retrieval that can accommodate new distance measures as they are developed by other research efforts. The work has application to medicine, art, photography, entertainment, and advertising/marketing.

本研究项目的目标是设计和实现一个基于内容的图像检索系统，该系统可以(1)提供各种各样的图像距离测量，可以单独使用或组合使用，以满足广泛的用户需求；(2)提供对图像的快速访问，即使是在一个非常大的数据库中。这项工作的重点是开发一种通用的、可扩展的体系结构，以支持对具有用户指定距离度量的大型图像数据库的快速查询。这包括开发与距离测量无关的算法和数据结构，以便从大型数据库中有效地检索图像。目前正在寻求将一般的、与距离度量无关的算法与其他可能特定于距离度量的有用技术（如关键字检索和关系索引）合并的方法。为用户提供多种不同种类的距离度量的问题正在研究中。正在设计将距离度量和一种语言结合起来的新方法，用户可以在不详细了解底层度量的情况下指定他们的查询。目前正在执行一个原型系统，以测试所开发的方法，并正在对一个大型一般图像数据库和一个较小的受控数据库进行评价。本研究的结果将是：(1)通过从搜索中消除图像数据库的大部分内容来促进图像快速检索的技术，使基于内容的检索在非常大且不断增长的数据库上可行；(2)采用新的高级方法，用户可以将距离度量组合起来形成有意义的查询，从而使基于内容的查询成为查询图像数据库的标准方式；(3)基于内容的检索的一般框架，可以适应其他研究工作开发的新距离度量。这项工作适用于医学、艺术、摄影、娱乐和广告/营销。