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Proceedings ArticleDOI

Content based image retrieval through object extraction and querying

TLDR
It is shown that the ability to access images at the level of objects is essential for CBIR, and the superiority of the approach over the global histogram approach is shown.
Abstract
We propose a content based image retrieval system based on object extraction through image segmentation. A general and powerful multiscale segmentation algorithm automates the segmentation process, the output of which is assigned novel colour and texture descriptors which are both efficient and effective. Query strategies consisting of a semi-automated and a fully automated mode are developed which are shown to produce good results. We then show the superiority of our approach over the global histogram approach which proves that the ability to access images at the level of objects is essential for CBIR.

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Citations
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Journal ArticleDOI

Complex Wavelets for Shift Invariant Analysis and Filtering of Signals

TL;DR: In this article, a dual tree of wavelet filters is proposed to obtain real and imaginary parts of the wavelet transform. And the dual tree can be extended for image and other multi-dimensional signals.
Journal ArticleDOI

Understanding Deep Learning Techniques for Image Segmentation

TL;DR: The main goal of this work is to provide an intuitive understanding of the major techniques that have made a significant contribution to the image segmentation domain.
Proceedings ArticleDOI

Is physics-based liveness detection truly possible with a single image?

TL;DR: This work proposes and validate a novel physics-based method to detect images recaptured from printed material using only a single image, and shows that the classifier can be generalizable to contrast enhanced recapture images and LCD screen recaptured images without re-training, demonstrating the robustness of the approach.
Journal ArticleDOI

Document retrieval from compressed images

TL;DR: Preliminary experimental results with the document images captured from students’ theses show that the proposed approach to retrieve the documents from CCITT Group 4 compressed document images has achieved a promising performance.
Posted Content

Understanding Deep Learning Techniques for Image Segmentation

TL;DR: In this article, the authors provide an intuitive understanding of the major techniques that have made significant contribution to the image segmentation domain, starting from some of the traditional segmentation approaches, the paper progresses describing the effect deep learning had on the Image Segmentation domain.
References
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Journal ArticleDOI

A Tutorial on Support Vector Machines for Pattern Recognition

TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Journal ArticleDOI

The estimation of the gradient of a density function, with applications in pattern recognition

TL;DR: Applications of gradient estimation to pattern recognition are presented using clustering and intrinsic dimensionality problems, with the ultimate goal of providing further understanding of these problems in terms of density gradients.
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.
Journal ArticleDOI

A multiscale random field model for Bayesian image segmentation

TL;DR: Simulations on synthetic images indicate that the new algorithm performs better and requires much less computation than MAP estimation using simulated annealing, and is found to improve classification accuracy when applied to the segmentation of multispectral remotely sensed images with ground truth data.
Journal ArticleDOI

Boundary detection by constrained optimization

TL;DR: A statistical framework is used for finding boundaries and for partitioning scenes into homogeneous regions and incorporates a measure of disparity between certain spatial features of block pairs of pixel gray levels, using the Kolmogorov-Smirnov nonparametric measures of difference between the distributions of these features.
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