We describe the Photobook system, which is a set of interactive tools for browsing and searching images and image sequences. These query tools differ from those used in standard image databases in that they make direct use of the image content rather than relying on text annotations. Direct search on image content is made possible by use of semantics-preserving image compression, which reduces images to a small set of perceptually-significant coefficients. We describe three types of Photobook descriptions in detail: one that allows search based on appearance, one that uses 2-D shape, and a third that allows search based on textural properties. These image content descriptions can be combined with each other and with textbased descriptions to provide a sophisticated browsing and search capability. In this paper we demonstrate Photobook on databases containing images of people, video keyframes, hand tools, fish, texture swatches, and 3-D medical data.

In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical ("Give me other images that contain a tumor with a texture like this one"), photo-journalism ("Give me images that have blue at the top and red at the bottom"), and many others in art, fashion, cataloging, retailing, and industry. We describe a set of novel features and similarity measures allowing query by color, texture, and shape of image object. We demonstrate the effectiveness of the QBIC system with normalized precision and recall experiments on test databases containing over 1000 images and 1000 objects populated from commercially available photo clip art images, and of images of airplane silhouettes. We also consider the efficient indexing of these features, specifically addre...

Abstract—Conventional database systems are designed for managing textual and numerical data, and retrieving such data is often based on simple comparisons of text/numerical values. However, this simple method of retrieval is no longer adequate for the multimedia data, since the digitized representation of images, video, or data itself does not convey the reality of these media items. In addition, composite data consisting of heterogeneous types of data also associates with the semantic content acquired by a user’s recognition. Therefore, content-based retrieval for multimedia data is realized taking such intrinsic features of multimedia data into account. Implementation of the content-based retrieval facility is not based on a single fundamental, but is closely related to an underlying data model, a priori knowledge of the area of interest, and the scheme for representing queries. This paper surveys recent studies on content-based retrieval for multimedia databases from the point of view of three fundamental issues. Throughout

A number of interfaces, based on different techniques which better exploit the human senses, have been recently suggested and implemented so enlarging the bandwith of the man-machine communication channel. The availability of graphical devices at low cost has given rise to a large diffusion of visual interfaces. The database field is particularly suited for such interfaces mainly because the database is often queried by a casual user, who may not be conversant with conventional query languages. The use of a visual tool may therefore help to access the database, without the dependency on the native language and the limitations imposed by the specific application area. In this paper we concentrate on the querying strategies developed in existing visual query systems (VQS) by defining a suitable taxonomy and analyzing how these systems can be compared against such a taxonomy. 1. Preliminaries The effective use of different complex application programs is strongly hindered by the required...

In this paper we propose a method to retrieve trademarks using query by sketches. The trademark images are first filtered to remove noise. Then each filtered image is segmented into regions based on pixel connectivity. For each region, a decision is made about whether thinning or edge extraction should be applied. Afterwards stroke tracing is performed to extract the sketch of the trademark. The user can then provide a query sketch that will be compared with those extracted sketches from the database trademark images in order to retrieve similar trademarks. Query by sketch is useful in the trademark retrieval application since the user can search for similar trademarks by providing a rough sketch instead of keywords. Our approach saves a lot of labor because it does not require the trademark database to be manually annotated with keywords. 1.

We describe the Photobook system, which is a set of interactive tools for browsing and searching images and image sequences. These query tools differ from those used in standard image databases in that they make direct use of the image content rather than relying on text annotations. Direct search on image content is made possible by use of semantics-preserving image compression, which reduces images to a small set of perceptually-significant coefficients. We describe three types of Photobook descriptions in detail: one that allows search based on appearance, one that uses 2-D shape, and a third that allows search based on textural properties. These image content descriptions can be combined with each other and with textbased descriptions to provide a sophisticated browsing and search capability. In this paper we demonstrate Photobook on databases containing images of people, video keyframes, hand tools, fish, texture swatches, and 3-D medical data. 1 Introduction: The Problem Digita...

The various relevant aspects for the retrieval of images present familiar documentation issues as well as some entirely new requirements. The Semantic Index System (SIS) has already been successfully employed in maintaining an evolving body of knowledge about the cultural and historical contexts of museum artifacts and multimedia documents(CLIO SYSTEM) . Its distinct features of runtime meta-modelling and classification of references satisfy the multiple classification needs for images and their parts and allow to access simultaneously through detailed annotations. Consequently, it integrates access methods through generic and specific indices and the relevant context. In this paper we present the principles and architecture of such a system as it is currently being implemented. 1. Introduction It is commonplace that images in any form, from sketches to photography to photorealistic representations, are important means of rendering human expression and documenting knowledge. Recent com...

Introduction Present methods of retrieving images based on visual content largely center around the extraction of certain salient features of an image, such as color, texture, shape, and the computation of a similarity measure between two images. Such methods, while effective in particularly focused applications, fail to generalize because they are semantically primitive when compared to human similarity judgment. Furthermore, most methods fail to exploit domain knowledge and relevance feedback to improve the accuracy of the search. These techniques, although commonly practiced in text-based retrieval systems, are lacking in content-based systems. Clearly, there is much more to be done in this area; we need to move towards a more intuitive, human-like query facility in order to allow laymen to use multimedia databases. In this article, we discuss the development of a multi-layered framework for visual information retrieval. In this framework, we integrate current works on cont

Recently, there has been widespread interest in various kinds of database management systems for managing information from images. Image Retrieval (IR) problem is concerned with retrieving images that are relevant to users' requests from a large collection of images, referred to as the image database. Since the application areas are very diverse, there seems to be no consensus as to what an image database system really is. Consequently, the features of the existing image database systems have essentially evolved from domain specific considerations. In response to this situation, we have introduced a unified framework for retrieval in image databases in [22]. Our approach to the image retrieval problem is based on the premise that it is possible to develop a data model and an associated retrieval model that can address the needs of a class of image retrieval applications. The key to domain independence is to separate the retrieval function from the image processing function. In this pap...