Object separation in x-ray image sets

@article{Heitz2010ObjectSI,
  title={Object separation in x-ray image sets},
  author={G. Heitz and Gal Chechik},
  journal={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  year={2010},
  pages={2093-2100}
}
  • G. Heitz, Gal Chechik
  • Published 2010
  • Computer Science
  • 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
In the segmentation of natural images, most algorithms rely on the concept of occlusion. In x-ray images, however, this assumption is violated, since x-ray photons penetrate most materials. In this paper, we introduce SATISφ, a method for separating objects in a set of x-ray images using the property of additivity in log space, where the log-attenuation at a pixel is the sum of the log-attenuations of all objects that the corresponding x-ray passes through. Our method leverages multiple… Expand
Handgun Detection in Single-Spectrum Multiple X-ray Views Based on 3D Object Recognition
TLDR
This work proposes to use a single-spectrum X-ray system for the detection of threat objects that can be recognized by analyzing the shape, such as handguns, and believes that it is possible to design an automated aid for the human inspection task using these computer vision algorithms. Expand
Visual Words on Baggage X-Ray Images
TLDR
It is concluded that although the straightforward application of BoW on X-ray images does not perform as well as it does on regular images, the performance can be significantly improved by utilizing the extra information available in X-Ray images. Expand
Improving the Accuracy of One-Shot Detectors for Small Objects in X-ray Images
TLDR
It was shown that the proposed algorithm with data augmentation leads to more precise results when compared to the conventional technique: the method outperforms the traditional approach by 5.4 - 25.7% depending on the type of used backbone convolutional neural network. Expand
X-Ray Testing by Computer Vision
  • D. Mery
  • Computer Science
  • 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops
  • 2013
TLDR
It is concluded that there are some areas -like casting inspection- where automated systems are very effective, and other application areas -such as baggage screening- where human inspection is still used, and there is some research in areas -including food analysis- where processes are beginning to be characterized by the use of X-ray imaging. Expand
Computer vision technology for X-ray testing
TLDR
There are some areas –like casting inspection where automated systems are very effective, and other application areas – such as baggage screening– where human inspection is still used; there are certain application areas–like weld and cargo inspections– where the process is semi-automatic; and there is some research in areas –including food analysis– where processes are beginning to be characterized by the use of X-ray imaging. Expand
X-ray Testing by Computer Vision Domingo Mery
X-ray imaging has been developed not only for its use in medical imaging for human beings, but also for materials or objects, where the aim is to analyze –nondestructively– those inner parts that areExpand
X-ray Testing : The State of the Art Domingo Mery
X-ray imaging has been developed not only for its use in medical imaging for human beings, but also for materials or objects, where the aim is to analyze –nondestructively– those inner parts that areExpand
Image Processing Methods for X-Ray Luggage Images: A Survey
The detection of threatening objects using x-ray luggage scan images has become an important means of aviation security nowadays. Although tremendous amount of efforts have been focused on automaticExpand
Multi-Spectral Imaging via Computed Tomography (MUSIC) - Comparing Unsupervised Spectral Segmentations for Material Differentiation
TLDR
The value of this dataset on the image analysis challenge of object segmentation purely based on the spectral response of its composing materials is demonstrated and the segmentation accuracy of fast adaptive mean shift (FAMS) and unconstrained graph cuts on both datasets are compared. Expand
X-ray Testing
TLDR
A general overview of computer vision approaches that have been used in X-ray testing is presented, and an introduction to the book is offered by covering relevant issues of X-rays testing. Expand
...
1
2
3
...

References

SHOWING 1-10 OF 32 REFERENCES
Improving the detection of low-density weapons in x-ray luggage scans using image enhancement and novel scene-decluttering techniques
TLDR
On-site quantitative and qualitative evaluations of the vari- ous decluttered images by airport screeners establishes that the single slice from the image hashing algorithm outperforms tradi- tional enhancement techniques with a noted increase of 58% in low- density threat detection rates. Expand
Layer extraction from multiple images containing reflections and transparency
  • R. Szeliski, S. Avidan, P. Anandan
  • Computer Science, Mathematics
  • Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662)
  • 2000
TLDR
This paper develops an optimal approach to recovering layer images and their associated motions from an arbitrary number of composite images and iteratively refines lower and upper bounds on the layer images using two novel compositing operations, namely minimum- and maximum-composites of aligned images. Expand
Three dimensional transparent structure segmentation and multiple 3D motion estimation from monocular perspective image sequences
  • Stefano Soatto, P. Perona
  • Mathematics
  • Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects
  • 1994
A three dimensional scene can be segmented using different cues, such as boundaries, texture, motion, discontinuities of the optical flow, stereo, models for structure, etc. We investigateExpand
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
Efficient Graph-Based Image Segmentation
TLDR
An efficient segmentation algorithm is developed based on a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image and it is shown that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties. Expand
Principles of computerized tomographic imaging
TLDR
Properties of Computerized Tomographic Imaging provides a tutorial overview of topics in tomographic imaging covering mathematical principles and theory and how to apply the theory to problems in medical imaging and other fields. Expand
Dense 3D Reconstruction of Specular and Transparent Objects Using Stereo Cameras and Phase-Shift Method
TLDR
It is shown that two viewpoints can uniquely determine the surface shape and surface normal by investigating the light path for each surface point by showing two-dimensional phase shifts on the display. Expand
Structure from motion without correspondence
TLDR
A method is presented to recover 3D scene structure and camera motion from multiple images without the need for correspondence information by means of an algorithm which iteratively refines a probability distribution over the set of all correspondence assignments. Expand
Shape and motion from image streams under orthography: a factorization method
TLDR
A factorization method is developed that can overcome the difficulty by recovering shape and motion under orthography without computing depth as an intermediate step, and gives accurate results. Expand
Algebraic reconstruction in CT from limited views.
  • A. H. Andersen
  • Mathematics, Medicine
  • IEEE transactions on medical imaging
  • 1989
TLDR
Computer simulation studies are presented which demonstrate significantly improved reconstructed images achieved by an ART algorithm as compared to IRR methods. Expand
...
1
2
3
4
...