| 1. |
- Felsberg, Michael, 1974-
(författare)
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On Second Order Operators and Quadratic Operators
- 2008
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : IEEE. - 9781424421756 - 9781424421749 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- In pattern recognition, computer vision, and image processing, many approaches are based on second order operators. Well-known examples are second order networks, the 3D structure tensor for motion estimation, and the Harris corner detector. A subset of second order operators are quadratic operators. It is lesser known that every second order operator can be written as a weighted quadratic operator. The contribution of this paper is to propose an algorithm for converting an arbitrary second order operator into a quadratic operator. We apply the method to several examples from image processing and machine learning. The advantages of the alternative implementation by quadratic operators is two-fold: The underlying linear operators allow new insights into the theory of the respective second order operators and replacing second order networks with sums of squares of linear networks reduces significantly the computational burden when the trained network is in operation phase.
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| 2. |
- Leinhard, Olof Dahlqvist, et al.
(författare)
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Quantitative Abdominal Fat Estimation Using MRI
- 2008
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : IEEE Computer Society. - 9781424421749 - 9781424421756 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a new method for automaticquantification of subcutaneous, visceral and nonvisceralinternal fat from MR-images acquired usingthe two point Dixon technique in the abdominal region.The method includes (1) a three dimensionalphase unwrapping to provide water and fat images, (2)an image intensity inhomogeneity correction, and (3) amorphon based registration and segmentation of thetissue. This is followed by an integration of the correctedfat images within the different fat compartmentsthat avoids the partial volume effects associated withtraditional fat segmentation methods. The method wastested on 18 subjects before and after a period of fastfoodhyper-alimentation showing high stability andperformance in all analysis steps.
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| 3. |
- Läthén, Gunnar, et al.
(författare)
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Phase Based Level Set Segmentation of Blood Vessels
- 2008
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Ingår i: Proceedings of 19th International Conference on Pattern Recognition. - : IEEE Computer Society. - 9781424421756 - 9781424421749 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- The segmentation and analysis of blood vessels hasreceived much attention in the research community. Theresults aid numerous applications for diagnosis andtreatment of vascular diseases. Here we use level setpropagation with local phase information to capture theboundaries of vessels. The basic notion is that localphase, extracted using quadrature filters, allows us todistinguish between lines and edges in an image. Notingthat vessels appear either as lines or edge pairs, weintegrate multiple scales and capture information aboutvessels of varying width. The outcome is a “global”phase which can be used to drive a contour robustly towardsthe vessel edges. We show promising results in2D and 3D. Comparison with a related method givessimilar or even better results and at a computationalcost several orders of magnitude less. Even with verysparse initializations, our method captures a large portionof the vessel tree.
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| 4. |
- Nordberg, Klas, 1963-
(författare)
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Efficient Triangulation Based on 3D Euclidean Optimization
- 2008
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Ingår i: International Conference on Pattern Recognition (ICPR). - : IEEE. - 9781424421749 - 9781424421756 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- This paper presents a method for triangulation of 3D points given their projections in two images. Recent results show that the triangulation mapping can be represented as a linear operator K applied to the outer product of corresponding homogeneous image coordinates, leading to a triangulation of very low computational complexity. K can be determined from the camera matrices, together with a so-called blind plane, but we show here that it can be further refined by a process similar to Gold Standard methods for camera matrix estimation. In particular it is demonstrated that K can be adjusted to minimize the Euclidean L, residual 3D error, bringing it down to the same level as the optimal triangulation by Hartley and Sturm. The resulting K optimally fits a set of 2D+2D+3D data where the error is measured in the 3D space. Assuming that this calibration set is representative for a particular application, where later only the 2D points are known, this K can be used for triangulation of 3D points in an optimal way, which in addition is very efficient since the optimization need only be made once for the point set. The refinement of K is made by iteratively reducing errors in the 3D and 2D domains, respectively. Experiments on real data suggests that very few iterations are needed to accomplish useful results.
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| 5. |
- Norell, Kristin, 1980-, et al.
(författare)
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Spatially-variant morphological operations on binary images based on the polar distance transform
- 2008
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Ingår i: ICPR 2008. - : IEEE computer society. - 9781424421756
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Konferensbidrag (refereegranskat)abstract
- Binary mathematical morphology can be computed by thresholding a distance transform, provided that the distance transform is a metric. Here we show that the polar distance transform is a metric and use it for morphological operations. The polar distance transform varies with the spatial coordinates of the image, resulting in spatially-variant morphology. In this distance transform each pixel is related to an image origin. We prefer angular propagation over radial, thus we construct structuring elements that are elongated in the angular direction, which is useful when circular segments are handled. We show an example where segments of annual rings on a log end face are connected using mathematical morphology based on the polar distance transform.
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| 6. |
- Rögnvaldsson, Thorsteinn, et al.
(författare)
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A self-organized approach for unsupervised fault detection in multiple systems
- 2008
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Ingår i: 19th International Conference on Pattern Recognition. - Piscataway, N.J. : IEEE Press. - 9781424421756 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- An approach is proposed for automatic fault detection in a population of mechatronic systems. The idea is to employ self-organizing algorithms that produce low-dimensional representations of sensor and actuator values on the vehicles, and compare these low-dimensional representations among the systems. If a representation in one vehicle is found to deviate from, or to be not so similar to, the representations for the majority of the vehicles, then the vehicle is labeled for diagnostics. The presented approach makes use of principal component coding and a measure of distance between linear sub-spaces. The method is successfully demonstrated using simulated data for a commercial vehiclepsilas engine coolant system, and using real data for computer hard drives.
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| 7. |
- Strand, Robin, 1978-, et al.
(författare)
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The Polar Distance Transform by Fast-Marching
- 2008
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Ingår i: Proceedings of 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, Florida, December 2008. - : IEEE computer society. - 9781424421756
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Konferensbidrag (refereegranskat)abstract
- Image analysis tools that process the image using polar coordinates are needed to avoid the interpolation from polar to cartesian coordinates. We present a tool for analysing and processing circular objects – the polar distance transform computed by fast-marching. The fast marching method can be used for computing the grey-weighted distance transform by numerically approximating the Eikonal differential equation. We modify the Eikonal equation using weights that depend on the radius and angle relative to a pre-defined coordinate system.
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| 8. |
- Viksten, Fredrik, 1976-, et al.
(författare)
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Point-of-Interest Detection for Range Data
- 2008
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Ingår i: International Conference on Pattern Recognition (ICPR). - : IEEE. - 9781424421756 - 9781424421749 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- Point-of-interest detection is a way of reducing the amount of data that needs to be processed in a certain application and is widely used in 2D image analysis. In 2D image analysis, point-of-interest detection is usually related to extraction of local descriptors for object recognition, classification, registration or pose estimation. In analysis of range data however, some local descriptors have been published in the last decade or so, but most of them do not mention any kind of point-of-interest detection. We here show how to use an extended Harris detector on range data and discuss variants of the Harris measure. All described variants of the Harris detector for 3D should also be usable in medical image analysis, but we focus on the range data case. We do present a performance evaluation of the described variants of the Harris detector on range data.
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