Results 181 to 190 of about 4,998 (209)

Saliency and Burstiness for Feature Selection in CBIR

2019 8th European Workshop on Visual Information Processing (EUVIP), 2019
The paper addresses the problem of visual feature selection in content-based image retrieval (CBIR). We propose to study two strategies: the first one is using visual saliency, that selects the most salient features of the image and the second one exploits burstiness, that detects and processes the repeated visual elements in the image.
Kamel Guissous, Valérie Gouet-Brunet
openaire   +2 more sources

Behaviour of Texture Features in a CBIR System

2008
Searching and processing in databases of general and non-specific images are highly subjective. The process of texture feature extraction from images produces results of highly theoretical and mathematical character that have little to do with human perception.
César Reyes, Maria Luisa Durán, Teresa Alonso, Pablo García Rodríguez, Andrés Caro   +4 more
openaire   +1 more source

Efficient and Flexible Cluster-and-Search for CBIR

2008
Content-Based Image Retrieval is a challenging problem both in terms of effectiveness and efficiency. In this paper, we present a flexible cluster-and-search approach that is able to reuse any previously proposed image descriptor as long as a suitable similarity function is provided.
Anderson Rocha 0001, Jurandy Almeida, Mario A. Nascimento, Ricardo da Silva Torres, Siome Goldenstein   +4 more
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A web-based evaluation system for CBIR

Proceedings of the 2001 ACM workshops on Multimedia multimedia information retrieval - MULTIMEDIA '01, 2001
This papers describes a benchmark test for content-based image retrieval systems (CBIRSs) with the query by example (QBE) query paradigm. This benchmark is accessible via the Internet and thus allows to evaluate any CBIRS which is compliant with Multimedia Retrieval Markup Language (MRML) for query formulation and result transmission.
Henning Müller, Wolfgang Müller 0001, David McG. Squire   +2 more
openaire   +2 more sources

A novel relevance feedback method for CBIR

World Wide Web, 2018
In this paper, we address the challenge about insufficiency of training set and limited feedback information in each relevance feedback (RF) round during the process of content based image retrieval (CBIR). We propose a novel active learning scheme to utilize the labeled and unlabeled images to build the initial Support Vector Machine (SVM) classifier ...
Yunbo Rao, Wei Liu 0073, Bojiang Fan, Jiali Song, Yang Yang   +4 more
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Texture element feature characterizations for CBIR

Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05., 2005
Colour and texture are the most common features used in CBIR systems today. In this paper, we wish to investigate structural methods of texture analysis for CBIR in view of their closeness to human perception and description of texture. In structural analysis, local patterns are the key (as is the case with humans), and when used as features may be ...
K. Jalaja, Chakravarthy Bhagvati, Bulusu Lakshmana Deekshatulu, Arun K. Pujari   +3 more
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Relevance feedback based saliency adaptation in CBIR

Multimedia Systems, 2005
Content-based image retrieval (CBIR) has been under investigation for a long time, with many systems built to meet different application demands. However, in all systems there is still a gap between user expectations and system retrieval capabilities. Therefore, user interaction is an essential component of any CBIR system.
Giang P. Nguyen, Marcel Worring
openaire   +4 more sources

Towards Automatic Detection of CBIRs Configuration

2012
Many Content Based Image Retrieval system s (CBIRs) have been invented in the last decade. The general mechanism of the search process is very similar for each of these CBIRs, and the calculation of rankings is determined by the comparison of features (low-, mid-, high-level).
Christian Vilsmaier, Rolf Karp, Mario Döller, Harald Kosch, Lionel Brunie   +4 more
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Comparison of different CBIR techniques

2011 3rd International Conference on Electronics Computer Technology, 2011
Image retrieval is a poor stepchild to other forms of information retrieval (IR). Image retrieval has been one of the most interesting and vivid research areas in the field of computer vision over the last decades. Content-Based Image Retrieval (CBIR) systems are used in order to automatically index, search, retrieve, and browse image databases.
Meenakshi Madugunki, D. S. Bormane, Sonali Bhadoria, C. G. Dethe   +3 more
openaire   +1 more source

An Efficient Indexing Algorithm for CBIR

2015 IEEE International Conference on Computational Intelligence & Communication Technology, 2015
Due to the continuous development of high quality multimedia technologies and rapid growth in the computational power along with availability of huge sized storage devices, digital image archives of very large size are being created day by day on the ever growing WWW through many commercial, research a development and academic web sites.
Md. Khalid Imam Rahmani, M.A. Ansari, Amit Kumar Goel   +2 more
openaire   +1 more source