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Content-Based Image Retrieval for Medical Image
2015 11th International Conference on Computational Intelligence and Security (CIS), 2015In 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 ...
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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
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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
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Advanced Content Based Image Retrieval for Fashion
2015In 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
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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
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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
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Preprocessing for content-based image retrieval. [PDF]
, 2009 The research focuses on image retrieval problems where the query is formed as an image of a specific object of interest. The broad aim is to investigate pre-processing for retrieval of images of objects when an example image containing the object is given. The object may be against a variety of backgrounds.
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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
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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
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Content-based image retrieval: A review of recent trends
Cogent Engineering, 2021Sadiq 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, 2022Shiv Ram Dubey
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Content-based image retrieval at the end of the early years
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000M Worring, Simone Santini
exaly