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Image Retrieval Based on Query by Saliency Content

Digital Signal Processing, 2015
In this research study we propose the query by saliency content retrieval (QSCR) image retrieval method which is based on human visual attention models. The proposed methodology represents a bottom-up approach considering the human attention, both locally at the level of image regions as well as globally, for the entire image. In the proposed retrieval
Alex Papushoy, Adrian G. Bors
openaire   +1 more source

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

Content-Based Image Retrieval for Medical Image

2015 11th International Conference on Computational Intelligence and Security (CIS), 2015
In this paper, the SIMPLIcity (Semantics-sensitive Integrate Matching for Picture Libraries), an image retrieval system is introduced. The feature extraction is based on Histogram, color layout and coefficients of wavelet transform. This retrieving system adopts feature database for matching so as to reduce the search space which is especially useful ...
openaire   +1 more source

Advanced Content Based Image Retrieval for Fashion

2015
In this paper we propose a new content based approach for clothing image retrieval trying to mimic the human vision understanding not only based on naive manipulation of texture and color, but also combining some recent and advanced techniques like human pose estimation, super-pixel segmentation and cloth parsing.
Dagnew, Tewodros Mulugeta   +1 more
openaire   +2 more sources

Content-based image retrieval

2008 6th International Symposium on Intelligent Systems and Informatics, 2008
A picture is worth a thousand words. Yes, but which ones? Content-based image retrieval (CBIR) is the application of computer vision to the image retrieval problem. The image retrieval problem is the problem of searching for digital images in large databases.
Igor Marinovic, Igor Furstner
openaire   +1 more source

Content-Based Image Retrieval

2009
Content-Based Image Retrieval (CBIR) aims to search images that are perceptually similar to the querybased on visual content of the images without the help of annotations. The current CBIR systems use global features (e.g., color, texture, and shape) as image descriptors, or usefeatures extracted from segmented regions (called region-based descriptors).
Ming Zhang, Reda Alhajj
openaire   +1 more source

Content-Based Image Retrieval

1995
As more and more image data are acquired and assume the role of “first-class citizens” in information technology, managing and manipulating them as images becomes an important issue to be resolved before we can take full advantage of their information content [CH92]. Image database and visual information system technologies have become major efforts to
Borko Furht   +2 more
openaire   +1 more source

Content-based image retrieval: A review of recent trends

Cogent Engineering, 2021
Sadiq H Abdulhussain   +2 more
exaly  

A Decade Survey of Content Based Image Retrieval Using Deep Learning

IEEE Transactions on Circuits and Systems for Video Technology, 2022
Shiv Ram Dubey
exaly  

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