Results 221 to 230 of about 64,555 (258)

A review of content-based image retrieval

2010 7th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), 2010
A comprehensive survey on patch recognition, which is a crucial part of content-based image retrieval (CBIR), is presented. CBIR can be viewed as a methodology in which three correlated modules including patch sampling, characterizing, and recognizing are employed.
Gholamreza Rafiee, Satnam Singh Dlay, Wai Lok Woo   +2 more
openaire   +1 more source

Content-based retrieval of ophthalmological images

Proceedings of 3rd IEEE International Conference on Image Processing, 2002
This paper describes steps towards an information system for the storage and content-based retrieval of ocular fundus images. Based on the Virage Incorporated framework for defining similarity metrics, the authors have developed a number of primitives for the representation of ocular fundus images.
Amarnath Gupta, Saied Moezzi, Adam L. Taylor, Shankar Chatterjee, Ramesh C. Jain, Michael H. Goldbaum, S. Burgess   +6 more
openaire   +1 more source

Content-based retrieval of segmented images

Proceedings of the second ACM international conference on Multimedia - MULTIMEDIA '94, 1994
Most general content-based image retrieval techniques use colour and texture as main retrieval indices. A recent technique uses colour pairs to model distinct object boundaries for retrieval. These techniques have been applied to overall image contents without taking into account the characteristics of individual objects. While the techniques work well
Tat-Seng Chua, S.-K. Lim, Hung Keng Pung
openaire   +1 more source

Content Based Image Retrieval Technique

2008
A retrieval methodology which integrates color, texture and shape information is presented in this paper. Consequently, the overall image similarity is developed through the similarity based on all the feature components. Alternatively to known CBIR systems, we compute features only in the finite number of extracted ROIs.
Ryszard S. Choras, Tomasz Andrysiak, Michal Choras   +2 more
openaire   +1 more source

A content-based image retrieval system

Image and Vision Computing, 1998
Abstract This paper proposes a Content-Based Images Retrieval (CBIR) system which uses a modified geometric hashing technique to retrieve similar shape images from the image database. The CBIR system is a two-stage image retrieval system: the outline-based image retrieval and the hash-table-based image retrieval.
Chung-Lin Huang, Dai-Hwa Huang
openaire   +1 more source

An introduction to content-based image retrieval

Eighth International Conference on Digital Information Management (ICDIM 2013), 2013
Content-based image retrieval (CBIR) extracts features from images to support image search. In this tutorial paper, we will review some of the basic CBIR algorithms that derive colour, texture and shape features, and will then show how image features can be extracted from the compressed domain, in particular from JPEG images, without the need of ...
openaire   +1 more source

Content-based image retrieval methods

Programming and Computer Software, 2009
Creation of a content-based image retrieval system implies solving a number of difficult problems, including analysis of low-level image features and construction of feature vectors, multidimensional indexing, design of user interface, and data visualization.
openaire   +1 more source

Content-based image retrieval

Multimedia Tools and Applications, 2023
Ciocca, G, Schettini, R, Santini, S, Bertini, M   +3 more
openaire   +3 more sources

Content Based Image Retrieval for Unsegmented Images

2003
We present a new method for image retrieval by shape similarity able to deal with real images with not uniform background and possible touching/occluding objects. First of all we perform a sketch-driven segmentation of the scene by means of a Deformation Tolerant version of the Generalized Hough Transform (DTGHT). Using the DTGHT we select in the image
Marco Anelli, Alessandro Micarelli, Enver Sangineto   +2 more
openaire   +2 more sources

Content based image retrieval with LIRe

Proceedings of the 19th ACM international conference on Multimedia, 2011
LIRe (Lucene Image Retrieval) is an open source library for content based image retrieval. Besides providing multiple common and state of the art retrieval mechanisms it allows for easy use on multiple platforms. LIRe is actively used for research, teaching and commercial applications.
openaire   +1 more source