Topic
Content-based image retrieval
About: Content-based image retrieval is a research topic. Over the lifetime, 6916 publications have been published within this topic receiving 150696 citations. The topic is also known as: CBIR.
Papers published on a yearly basis
Papers
More filters
TL;DR: The goal of the project is the implementation of an open visual information retrieval prototype as basis for further research on major problems of VIR, and the intended design of the querying framework, the user interface design and major implementation issues are described.
Abstract: In this paper the visual information retrieval project VizIR is presented. The goal of the project is the implementation of an open visual information retrieval (VIR) prototype as basis for further research on major problems of VIR. The motivation behind VizIR is the implementation of an open platform for supporting and facilitating research, teaching, the exchange of research results and research cooperation in the field in general. The availability of this platform could make cooperation and such research (especially for smaller institutions) easier. The intention of this paper is to inform interested researchers about the VizIR project and its design and to invite people to participate in the design and implementation process. We describe the goals of the VizIR project, the intended design of the querying framework, the user interface design and major implementation issues. The querying framework consists of classes for feature extraction, similarity measurement, media handling and database access. User interface design includes a description of visual components and their class structure, the communication between panels and the communication between visual components and query engines. The latter is based on the multimedia retrieval markup language (MRML, Website. http://www.mrml.net (last visited: 2003–03–20)). To be compatible with our querying paradigm, we extend MRML with additional elements. Implementation issues include a sketch on advantages and drawbacks of existing cross-platform media processing frameworks: Java Media Framework, OpenML and DirectX/DirectShow and details on the Java components used for user interface implementation, 3D graphics with Java and Java XML parsing.
29 citations
01 Jan 2013
TL;DR: In this article, the authors explore the CBIR techniques and their usage in various application domains and explore the use of CBIR for browsing, searching and retrieving images from a large database of digital images.
Abstract: As image collections are growing at a rapid rate, demand for efficient and effective tools for retrieval of query images from database is increased significantly. Among them, content-based image retrieval systems (CBIR) have become very popular for browsing, searching and retrieving images from a large database of digital images as it requires relatively less human intervention. This paper is an attempt to explore the CBIR techniques and their usage in various application domains.
29 citations
TL;DR: Evidence is found that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution.
29 citations
24 Mar 1999
TL;DR: The problem from the point of view of real-world system construction is presented, the main feature extraction methods used in modern CBIR systems are discussed, and several CBIR system implementations are outlined.
Abstract: The ability to organize and retrieve visual information such as images and video is becoming a crucial problem for specialists and general computer users alike. Because processing visual information requires perceptual abilities not yet known to exist in computational form, the ability to retrieve visual information without human assistance is a rich, complex, and interesting problem. This paper presents the problem from the point of view of real-world system construction, discusses the main feature extraction methods used in modern CBIR systems, and outlines several CBIR system implementations.
29 citations
09 Aug 2015
TL;DR: This work aims at the task of retrieving images that are visually and semantically similar to a given example image; the system should be able to online evaluate k nearest neighbor queries within a collection containing tens of millions of images.
Abstract: One of current big challenges in computer science is
development of data management and retrieval techniques that
would keep pace with the evolution of contemporary data and
with the growing expectations on data processing. Various
digital images became a common part of both public and
enterprise data collections and there is a natural requirement
that the retrieval should consider more the actual visual
content of the image data. In our demonstration, we aim at the
task of retrieving images that are visually and semantically
similar to a given example image; the system should be able to
online evaluate k nearest neighbor queries within a collection
containing tens of millions of images. The applicability of
such a system would be, for instance, on stock photography
sites, in e-shops searching in product photos, or in
collections from a constrained Web image search.
29 citations