Exploring Image Data-Bases Using Novel Similarity Metrics

大容量存储器价格的持续下降和计算机网络，特别是因特网的广泛使用，使大量用户能够接触到大量的信息。这些信息大多是图像，通常是以数字形式存储的普通图像。然而，用于组织、浏览和查询这些图像数据的工具并没有跟上可用信息的数量。本研究开发了一种基于图像和其他图形数据的外观，更具体地说是基于它们的颜色、形状和纹理内容来总结和索引图像和其他图形数据的新方法。这些描述符称为图像签名，它们是统一的、紧凑的、灵活的、健壮的和直观的。引入了特征间距离的概念，并将其用于图像空间的度量结构。这个度量结构，连同额外的几何信息，然后被利用来提供有效的最近邻搜索算法，以及计算距离保持嵌入的图像空间，或其部分，到一个低维欧几里德空间。使用多维尺度获得的这种嵌入，使用户可以直观地看到感兴趣的局部图像邻域或整个图像空间。用户能够直观地在图像空间中导航，具有连续性和全面性，而不像当前的系统通常以不连贯的方式呈现数据库的片段。然后，这些工具为探索图像数据库提供了一种新颖的隐喻，使其更类似于熟悉的图书馆或书店浏览。

Continued reductions in the prices of mass storage and widespread access to computer networks, especially the Internet, have given a large number of users access to vast amounts of information. Much of this information is pictorial, often ordinary images stored in digital form. Yet the tools available for organizing, browsing, and interrogating such image data have not kept pace with the volume of information made available. This research develops a novel way of summarizing and indexing images and other pictorial data based on their appearance, and more specifically on their color, shape, and texture content. These descriptors, called image signatures, are uniform, compact, flexible, robust, and intuitive. The notion of the Earth-Mover's Distance between signatures is introduced and used to give a metric structure to the image space. This metric structure, together with additional geometric information, is then exploited to provide efficient nearest-neighbor search algorithms, as well as to compute distance-preserving embeddings of the image space, or portions thereof, into a low-dimensional Euclidean space. Such embeddings, obtained using multi-dimensional scaling, allow the user to visualize intuitively both local image neighborhoods of interest, or the entire image space at once. The user is able to navigate around the image space intuitively, with a sense of continuity and comprehensiveness, unlike current systems which typically present fragments of the data-base in a disconnected fashion. These tools then enable a novel metaphor for exploring image data- bases, making it more akin to the familiar browsing of a library or a bookstore.