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Content-Based Image Retrieval in Astronomy

Information Retrieval, 2000
Summary: Content-based image retrieval in astronomy needs methods that can deal with an image content made of noisy and diffuse structures. This motivates investigations on how information should be summarized and indexed for this specific kind of images.
AndrĂ© Csillaghy   +2 more
openaire   +3 more sources

Faceted Content-Based Image Retrieval

2008 19th International Conference on Database and Expert Systems Applications, 2008
In typical content-based image retrieval systems it is not possible to navigate the image space by simultaneously applying multiple similarity criteria. The model we propose addresses this problem by representing the search for the images similar to a given image as the exploration of a lattice of (non-disjoint) image clusters, induced by a natural ...
Amato G, Meghini C
openaire   +4 more sources

Content based image and video retrieval

SPIE Proceedings, 2010
The growing capacity of computers, the abundance of digital cameras and the increased connectivity of the world all point to large digital multimedia archives. They include images and videos from the World Wide Web, museum objects, flowers, trademarks, and views from everyday life.
Shubhangi H. Patil   +4 more
openaire   +2 more sources

Content-based image retrieval

SPIE Proceedings, 2010
Large collection of information is being created in many areas of modern life on daily basis. This information exists in many forms from plain text to high resolution multimedia. Today computers are many times faster than human in text based searching using keywords and indexing but the story is totally different in case of multimedia.
openaire   +2 more sources

Content Based Image Retrieval with Hadoop

2016
Hadoop has become a widely used open source framework for large scale data processing. MapReduce is the core component of Hadoop. It is this programming paradigm that allows for massive scalability across hundreds or thousands of servers in a Hadoop cluster. It allows processing of extremely large video files or image files on data nodes.
Heba Gaber   +3 more
openaire   +2 more sources

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

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   +2 more
openaire   +2 more sources

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   +6 more
openaire   +2 more sources

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   +2 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
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