Open Access
Features in Content-based Image Retrieval Systems: a Survey.
Remco C. Veltkamp,Mirela Tanase,Danielle Sent +2 more
- pp 97-124
TLDR
This article provides a framework to describe and compare content-based image retrieval systems, in terms of the following technical aspects: querying, relevance feedback, result presentation, features, and matching.Abstract:
This article provides a framework to describe and compare content-based image retrieval systems. Sixteen contemporary systems are described in detail, in terms of the following technical aspects: querying, relevance feedback, result presentation, features, and matching. For a total of 44 systems we list the features that are used. Of these systems, 35 use any kind of color features, 28 use texture, and only 25 use shape features.read more
Citations
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Journal ArticleDOI
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
Julia Vogel,Bernt Schiele +1 more
TL;DR: A novel image representation is presented that renders it possible to access natural scenes by local semantic description by using a perceptually plausible distance measure that leads to a high correlation between the human and the automatically obtained typicality ranking.
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Histology image analysis for carcinoma detection and grading
TL;DR: An overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification is presented and emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification.
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Region-based image retrieval using integrated color, shape, and location index
TL;DR: Results obtained show that retrieval effectiveness increases in non-cascaded region-based querying by combined index, and also based on a combined color shape location index.
Proceedings ArticleDOI
A comparative study of similarity measures for content-based multimedia retrieval
TL;DR: This paper compares major state-of-the-art similarity measures applicable to flexible feature signatures with respect to their qualities of effectiveness and efficiency and study the behavior of the similarity measures by discussing their properties.
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Polygonal Modeling of Contours of Breast Tumors With the Preservation of Spicules
TL;DR: An index of spiculation derived from the turning functions of the polygonal models obtained by the proposed method yields better classification accuracy than a similar measure derived using a previously published method.
References
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Journal ArticleDOI
Textural Features Corresponding to Visual Perception
TL;DR: The discrepancies between human vision and computerized techniques that are encountered in this study indicate fundamental problems in digital analysis of textures and could be overcome by analyzing their causes and using more sophisticated techniques.
Journal ArticleDOI
Image Retrieval
TL;DR: The survey includes 100+ papers covering the research aspects of image feature representation and extraction, multidimensional indexing, and system design, three of the fundamental bases of content-based image retrieval.
Proceedings ArticleDOI
QBIC project: querying images by content, using color, texture, and shape
Carlton Wayne Niblack,R. Barber,Will Equitz,Myron D. Flickner,Eduardo H. Glasman,Dragutin Petkovic,Peter Cornelius Yanker,Christos Faloutsos,Gabriel Taubin +8 more
TL;DR: The main algorithms for color texture, shape and sketch query that are presented, show example query results, and discuss future directions are presented.
Book ChapterDOI
Blobworld: A System for Region-Based Image Indexing and Retrieval
TL;DR: This work indexes the blob descriptions using a lower-rank approximation to the high-dimensional distance to make large-scale retrieval feasible, and shows encouraging results for both querying and indexing.
Proceedings ArticleDOI
NeTra: a toolbox for navigating large image databases
Wei-Ying Ma,B.S. Manjunath +1 more
TL;DR: An implementation of NeTra, a prototype image retrieval system that uses color, texture, shape and spatial location information in segmented image regions to search and retrieve similar regions from the database, is presented.