Efficient Content-Based Image Retrieval

本研究计画的目标是设计并实作一个系统，以进行以内容为基础的影像撷取，它可以提供大量的影像距离测量，可以单独使用或结合使用，以满足广泛的使用者需求，以及提供快速的影像存取，即使是在一个非常大的资料库中。工作的重点是开发一个通用的，可扩展的体系结构，以支持快速查询非常大的图像数据库与用户指定的距离措施。这包括开发独立于距离测量的算法和数据结构，以便从大型数据库中进行有效的图像检索。正在寻求将一般的、独立于距离度量的算法与可能是距离度量特定的其他有用技术（例如关键字检索和关系索引）合并的方法。目前正在研究向用户提供许多不同种类的多种距离量度的问题。正在设计新的方法，用于结合距离测量和一种语言，用户可以在不详细了解基本指标的情况下指定他们的查询。一个原型系统正在实施，以测试开发的方法，和评价正在进行一个大型的通用图像数据库和一个较小的控制数据库。这项研究的结果将是：（1）通过从搜索中消除图像数据库的巨大部分来促进图像的快速检索的技术，使得基于内容的检索在非常大的和不断增长的数据库上可行;（2）新的、高级的方法，用户可以通过该方法联合收割机距离测量来形成有意义的查询，使得基于内容的查询可以成为查询图像数据库的标准方式;和（3）一个基于内容的检索，可以容纳新的距离措施，因为他们是由其他研究工作开发的一般框架。该作品可应用于医学、艺术、摄影、娱乐和广告/营销。

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.