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Image databases: Using perceptual organization, color and texture for retrieval in digital libraries.

机译:图像数据库:使用感知组织,颜色和纹理在数字图书馆中进行检索。

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The focus of this research is to develop a comprehensive framework for content-based retrieval in digital image libraries. Most of the current techniques in image retrieval are oriented towards lower-level processing of image data (pixel color histogram and image texture analysis). These techniques rarely analyze an image for the extraction of higher-level semantic features that describe the structural content of an image. Perceptual organization, grouping and inference principles are used in this work for the extraction of semantic information exhibited in the form of image structure. The usefulness of higher-level features for the retrieval of images containing manmade objects, such as buildings, towers, bridges, and architectural objects, is studied and demonstrated. Their utility is also exploited in a general framework for image retrieval, where queries are served by a retrieval methodology composed of both lower-level and higher-level analyses. The synergy resulting from this combination helps in successfully retrieving a wide variety of images, including those containing natural objects such as trees, water, sky, mountains, animals, and landscapes.; In addition, this dissertation presents perceptual constancy in grouping and organization as the link between perception, geometry and transformation. The perceptual organizational phenomenon of shape constancy is used as a key idea in representing structural similarity. A unified representation of structural similarity as a concept of invariance over the group of Euclidean similarity transformations is presented. A similarity-invariant model of perceptual organization and grouping is derived, and its applications are considered. The retrieval process is also examined using a mathematical model of isotropic and anisotropic mappings.; Users in many fields are exploiting the opportunities offered by the ability to access and manipulate collections of digital images. They include people from diverse disciplines, such as medicine, architecture, engineering, fashion, graphic design, publishing, crime prevention, as well as ordinary users on the internet. The developed system has applications in the manipulation and organization of images in digital archives and the World-Wide-Web (WWW), serving the needs of a large number of users.
机译:这项研究的重点是为数字图像库中基于内容的检索开发一个全面的框架。当前图像检索中的大多数技术都面向图像数据的低级处理(像素颜色直方图和图像纹理分析)。这些技术很少分析图像以提取描述图像结构内容的高级语义特征。在这项工作中,使用感知组织,分组和推理原理来提取以图像结构形式展示的语义信息。研究并展示了高级功能对于检索包含人造对象(例如建筑物,塔楼,桥梁和建筑对象)的图像的有用性。在通用的图像检索框架中还利用了它们的效用,在该框架中,查询由包含低层和高层分析的检索方法提供服务。这种结合产生的协同作用有助于成功检索各种图像,包括那些包含自然物体(例如树木,水,天空,山脉,动物和风景)的图像。另外,本文提出了感知和几何,变换之间联系的分组和组织感知一致性。形状恒定的感知组织现象被用作代表结构相似性的关键思想。提出了结构相似性的统一表示形式,作为欧几里得相似性变换组上不变性的概念。推导了感知组织和分组的相似性不变模型,并考虑了其应用。还使用各向同性和各向异性映射的数学模型检查了检索过程。许多领域的用户正在利用访问和操纵数字图像集合的能力所提供的机会。他们包括医学,建筑,工程,时装,图形设计,出版,犯罪预防等不同学科的人员,以及互联网上的普通用户。所开发的系统在数字档案和万维网(WWW)中的图像处理和组织中具有应用程序,可满足大量用户的需求。

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