Content-based Image Retrieval by a Fuzzy Scale-space Approach

@article{Ceccarelli2006ContentbasedIR,
  title={Content-based Image Retrieval by a Fuzzy Scale-space Approach},
  author={Michele Ceccarelli and Francesco Musacchia and Alfredo Petrosino},
  journal={Int. J. Pattern Recognit. Artif. Intell.},
  year={2006},
  volume={20},
  pages={849-868}
}
Image descriptions aimed at the realization of content-based image retrieval (CBIR) should include the vagueness of both data representations and user queries. Here we show how multiscale textural gradient can be used as an efficient visual cue for image description. This feature has been already efficiently used in problems of image segmentation and texture separation. Our main idea is based on the assumption that, for image description, shape and textures should be considered together within… 

Figures from this paper

Efficient Shape-Based Image Retrieval Based on Gray Relational Analysis and Association Rules
TLDR
An improved shape based image retrieval strategy based on gray relational analysis and association rules is proposed, which can further reveal users' image searching behavior.
A HYBRID TECHNIQUE FOR CONTENT BASED IMAGE RETRIEVAL USING DWT AND MODIFIED K-MEANS
TLDR
Algorithms on the basis of texture, shape, and color based feature extraction and matching of color and texture, and modified K-Means clustering are proposed, which is more optimized for small as well as large database.
An Ontology-Based Model for Representing Image Processing Application Objectives
This paper investigates the types of information that are necessary and sufficient to design and evaluate image processing software programs, and proposes a representation of these information
An Ontology-Based Model for Representing Image Processing Objectives
This paper investigates what kinds of information are necessary and sufficient to design and evaluate image processing software programs and proposes a representation of these information elements

References

SHOWING 1-10 OF 85 REFERENCES
A Fuzzy Scale-Space Approach to Feature-Based Image Representation and Retrieval
We propose an image indexing and retrieval method which is based on the multiscale image analysis theory in conjunction with fuzzy image feature extraction. The main idea is based on the assumption
Content-based image retrieval based on a fuzzy approach
TLDR
It is discussed how fuzzy set theory can be effectively used for this purpose and an image retrieval system called FIRST (fuzzy image retrieved system) which incorporates many of these ideas is described.
Image retrieval using color and shape
Multiresolution similarity search in image databases
TLDR
A new generalized similarity search method based on a wavelet transformation of the color histograms and a new effectiveness measure for image similarity search that is more general and more effective than previous approaches while retaining a competitive performance is shown.
Content-based image indexing and searching using Daubechies' wavelets
TLDR
WBIIS (Wavelet-Based Image Indexing and Searching), a new image indexing and retrieval algorithm with partial sketch image searching capability for large image databases, which performs much better in capturing coherence of image, object granularity, local color/texture, and bias avoidance than traditional color layout algorithms.
Content-Based Image Database Retrieval Using Variances of Gray Level Spatial Dependencies
TLDR
This paper discusses how variances of gray level spatial dependencies as textural features to retrieve images having some section in them that is like the user input image, and argues that some of the assignments which are counted as incorrect are not in fact incorrect.
Content-Based Image Retrieval at the End of the Early Years
TLDR
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.
...
...