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Private Content Based Image Retrieval
2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008For content level access, very often database needs the query as a sample image. However, the image may contain private information and hence the user does not wish to reveal the image to the database. Private content based image retrieval (PCBIR) deals with retrieving similar images from an image database without revealing the content of the query ...
Jagarlamudi Shashank +3 more
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A review of content-based image retrieval
2010 7th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), 2010A 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
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Content-based retrieval of ophthalmological images
Proceedings of 3rd IEEE International Conference on Image Processing, 2002This 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
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Content-based retrieval of segmented images
Proceedings of the second ACM international conference on Multimedia - MULTIMEDIA '94, 1994Most 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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Content Based Image Retrieval Technique
2008A 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
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A content-based image retrieval system
Image and Vision Computing, 1998Abstract 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
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An introduction to content-based image retrieval
Eighth International Conference on Digital Information Management (ICDIM 2013), 2013Content-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 ...
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Content-based image retrieval methods
Programming and Computer Software, 2009Creation 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.
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Content image retrieval based on topological information
Journal of Visual Languages & Computing, 2004Abstract In this paper a novel scheme for representing topological features extracted from image database is proposed. The scheme utilizes a geometry-based structure that represents each image by means a string containing information on a polygonal associated with the pictorial scene.
F. CANNAVALE +3 more
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