Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing

@article{Berretti2000RetrievalBS,
  title={Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing},
  author={Stefano Berretti and A. Bimbo and Pietro Pala},
  journal={IEEE Trans. Multim.},
  year={2000},
  volume={2},
  pages={225-239}
}
An important problem in accessing and retrieving visual information is to provide efficient similarity matching in large databases. Though much work is being done on the investigation of suitable perceptual models and the automatic extraction of features, little attention is given to the combination of useful representations and similarity models with efficient index structures. In this paper we propose retrieval by shape similarity using local descriptors and effective indexing. Shapes are… 

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References

SHOWING 1-10 OF 43 REFERENCES

Visual Image Retrieval by Elastic Matching of User Sketches

  • A. BimboP. Pala
  • Computer Science
    IEEE Trans. Pattern Anal. Mach. Intell.
  • 1997
TLDR
A technique which is based on elastic matching of sketched templates over the shapes in the images to evaluate similarity ranks and is integrated with arrangements to provide scale invariance and take into account spatial relationships between objects in multi-object queries.

Efficient and Robust Retrieval by Shape Content through Curvature Scale Space

We introduce a very fast and reliable method for shape similarity retrieval in large image databases which is robust with respect to noise, scale and orientation changes of the objects. The maxima of

Efficient retrieval by shape content

TLDR
The heart of the methodology is a a dynamic programming shape matching algorithm which detects similarities between shapes at various levels of shape detail (resolution) and provides for indexing of a data set, achieving up to three orders of magnitude speed-up over sequential scanning.

Image retrieval using color and shape

Similar-Shape Retrieval in Shape Data Management

TLDR
This work discusses the central issues in similar-shape retrieval and explains how these issues are resolved in a shape retrieval scheme called FIBSSR (Feature Index-Based Similar-Shape Retrieval).

Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval

TLDR
The Wold model appears to offer a perceptually more satisfying measure of pattern similarity while exceeding the performance of these other methods by traditional pattern recognition criteria.

Shape retrieval based on dynamic programming

TLDR
A shape matching algorithm for deformed shapes based on dynamic programming that is capable of grouping together segments at finer scales in order to come up with appropriate correspondences with segments at coarser scales is proposed.

Similarity indexing with the SS-tree

  • David A. WhiteR. Jain
  • Computer Science
    Proceedings of the Twelfth International Conference on Data Engineering
  • 1996
TLDR
This work describes the fundamental types of "similarity queries" that should be supported and proposes a new dynamic structure for similarity indexing called the similarity search tree or SS-tree, which performs better than the R*-tree in nearly every test.