Corpus ID: 5271512

Content Based Image Retrieval using Color Boosted Salient Points and Shape features of an image

@inproceedings{HiremathP2008ContentBI,
  title={Content Based Image Retrieval using Color Boosted Salient Points and Shape features of an image},
  author={S HiremathP. and Jagadeesh D. Pujari},
  year={2008}
}
Salient points are locations in an image where there is a significant variation with respect to a chosen image feature. Since the set of salient points in an image capture important local characteristics of that image, they can form the basis of a good image representation for content-based image retrieval (CBIR). Salient features are generally determined from the local differential structure of images. They focus on the shape saliency of the local neighborhood. Most of these detectors are… Expand

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References

SHOWING 1-10 OF 18 REFERENCES
Boosting color saliency in image feature detection
The aim of salient feature detection is to find distinctive local events in images. Salient features are generally determined from the local differential structure of images. They focus on theExpand
IRM: integrated region matching for image retrieval
TLDR
The IRM measure for evaluating overall similarity between images incorporates properties of all the regions in the images by a region-matching scheme, which achieves more accurate retrieval at higher speed than several existing systems. Expand
Combine user defined region-of-interest and spatial layout for image retrieval
TLDR
A novel approach combining a user defined region-of-interest and spatial layout is proposed for CBIR and better capture of the image object is achieved by the user rather than the computer, which lends to a more powerful search engine. Expand
Localized Content-Based Image Retrieval
TLDR
A localized CBIR system that uses labeled images in conjunction with a multiple-instance learning algorithm to first identify the desired object and weight the features accordingly, and then to rank images in the database using a similarity measure that is based upon only the relevant portions of the image. Expand
PicToSeek: combining color and shape invariant features for image retrieval
TLDR
It is concluded that object retrieval based on composite color and shape invariant features provides excellent retrieval accuracy and the image retrieval scheme is highly robust to partial occlusion, object clutter and a change in the object's pose. Expand
A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval
TLDR
A fuzzy logic approach, UFM (unified feature matching), for region-based image retrieval, which greatly reduces the influence of inaccurate segmentation and provides a very intuitive quantification. Expand
Review of shape representation and description techniques
TLDR
This paper identifies some promising techniques for image retrieval according to standard principles and examines implementation procedures for each technique and discusses its advantages and disadvantages. Expand
Robust texture features for still-image retrieval
TLDR
A detailed evaluation of the use of texture features in a query-by-example approach to image retrieval is presented, demonstrating that they provide robust performance across a range of datasets. Expand
Texture Features for Browsing and Retrieval of Image Data
TLDR
Comparisons with other multiresolution texture features using the Brodatz texture database indicate that the Gabor features provide the best pattern retrieval accuracy. Expand
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
TLDR
Results indicating that querying for images using Blobworld produces higher precision than does querying using color and texture histograms of the entire image in cases where the image contains distinctive objects are presented. Expand
...
1
2
...