Journal ArticleDOI
A Survey on Current Content based Image Retrieval Methods
TLDR
The survey includes a large number of papers covering the research aspects of system design and applications of CBIR, image feature representation and extraction, Multidimensional indexing, and future research directions are suggested.Abstract:
Retrieving information from the Web is becoming a common practice for internet users. However, the size and heterogeneity of the Web challenge the effectiveness of classical information retrieval techniques. Content-based retrieval of images and video has become a hot research area. The reason for this is the fact that we need effective and efficient techniques that meet user requirements, to access large volumes of digital images and video data. This paper gives a brief survey of current CBIR (Content Based Image Retrieval) methods and technical achievement in this area. The survey includes a large number of papers covering the research aspects of system design and applications of CBIR, image feature representation and extraction, Multidimensional indexing. Furthermore future research directions are suggested.read more
Citations
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The Self-Organizing Map
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Journal ArticleDOI
Local Tetra Patterns: A New Feature Descriptor for Content-Based Image Retrieval
TL;DR: A novel image indexing and retrieval algorithm using local tetra patterns (LTrPs) for content-based image retrieval (CBIR) that encodes the relationship between the referenced pixel and its neighbors, based on the directions that are calculated using the first-order derivatives in vertical and horizontal directions.
Journal ArticleDOI
Texture image retrieval using new rotated complex wavelet filters
TL;DR: A novel approach for texture image retrieval is proposed by using a set of dual-tree rotated complex wavelet filter (DT-RCWF) andDual-tree-complex wavelet transform ( DT-CWT) jointly, which obtains texture features in 12 different directions.
Journal ArticleDOI
Local maximum edge binary patterns: A new descriptor for image retrieval and object tracking
TL;DR: A new algorithm meant for content based image retrieval (CBIR) and object tracking applications is presented, which differs from the existing LBP in a manner that it extracts the information based on distribution of edges in an image.
Journal ArticleDOI
Local Mesh Patterns Versus Local Binary Patterns: Biomedical Image Indexing and Retrieval
TL;DR: A new image indexing and retrieval algorithm using local mesh patterns are proposed for biomedical image retrieval application that shows a significant improvement in terms of their evaluation measures as compared to LBP, LBP with Gabor transform, and other spatial and transform domain methods.
References
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Proceedings ArticleDOI
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Journal ArticleDOI
Content-based image retrieval at the end of the early years
TL;DR: The working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap are discussed, as well as aspects of system engineering: databases, system architecture, and evaluation.
Proceedings ArticleDOI
The R*-tree: an efficient and robust access method for points and rectangles
TL;DR: The R*-tree is designed which incorporates a combined optimization of area, margin and overlap of each enclosing rectangle in the directory which clearly outperforms the existing R-tree variants.
Journal ArticleDOI
Comparing images using the Hausdorff distance
TL;DR: Efficient algorithms for computing the Hausdorff distance between all possible relative positions of a binary image and a model are presented and it is shown that the method extends naturally to the problem of comparing a portion of a model against an image.