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| 3. |
- Curic, Vladimir, 1981-, et al.
(författare)
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Distance measures between digital fuzzy objects and their applicability in image processing
- 2011
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Ingår i: Combinatorial Image Analysis. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642210723 ; 6636, s. 385-397
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Konferensbidrag (refereegranskat)abstract
- We present two different extensions of the Sum of minimal distances and the Complement weighted sum of minimal distances to distances between fuzzy sets. We evaluate to what extent the proposed distances show monotonic behavior with respect to increasing translation and rotation of digital objects, in noise free, as well as in noisy conditions. Tests show that one of the extension approaches leads to distances exhibiting very good performance. Furthermore, we evaluate distance based classification of crisp and fuzzy representations of objects at a range of resolutions. We conclude that the proposed distances are able to utilize the additional information available in a fuzzy representation, thereby leading to improved performance of related image processing tasks.
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| 4. |
- Curic, Vladimir, 1981-, et al.
(författare)
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The Sum of minimal distances as a useful distance measure for image registration
- 2010
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Ingår i: Proceedings SSBA 2010. - Uppsala : Centre for Image Analysis. ; , s. 55-58
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we study set distances which are used in image registration related problems. We introduced a new distance as a Sum of minimal distances with added linear weights. Linear weights are added in a way to reduce the impact of single outliers. An evaluation of observed distances with respect to applicability to image object registration is performed. A comparative study of set distances with respect to noise sensitivity as well as with respect to translation and rotation of objects in image is presented. Based on our experiments on synthetic images containing various types of noise, we determine that the proposed weighted sum of minimal distances has a good performances for object registration.
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| 5. |
- Dražić, Slobodan, et al.
(författare)
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Precise Estimation of the Projection of a Shape from a Pixel Coverage Representation
- 2011
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Ingår i: Proceedings of the 7th IEEE International Symposium on Image and Signal Processing and Analysis (ISPA). - : IEEE Computer Society. - 9781457708411 ; , s. 569-574, s. 569-574
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Konferensbidrag (refereegranskat)abstract
- Measuring width and diameter of a shape areproblems well studied in the literature. A pixel coverage repre-sentation is one specific type of digital fuzzy representation of acontinuous image object, where the (membership) value of eachpixel is (approximately) equal to the relative area of the pixelwhich is covered by the continuous object. Lately a number ofmethods for shape analysis use pixel coverage for reducing errorof estimation. We introduce a novel method for estimating theprojection of a shape in a given direction. The method is based onutilizing pixel coverage representation of a shape. Performance ofthe method is evaluated by a number of tests on synthetic objects,confirming high precision and applicability for calculation ofdiameter and elongation of a shape.
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| 7. |
- Lindblad, Joakim, et al.
(författare)
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Coverage segmentation based on linear unmixing and minimization of perimeter and boundary thickness
- 2012
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Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 33:6, s. 728-738
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Tidskriftsartikel (refereegranskat)abstract
- We present a method for coverage segmentation, where the, possibly partial, coverage of each image element by each of the image components is estimated. The method combines intensity information with spatial smoothness criteria. A model for linear unmixing of image intensities is enhanced by introducing two additional conditions: (i) minimization of object perimeter, leading to smooth object boundaries, and (ii) minimization of the thickness of the fuzzy object boundary, and to some extent overall image fuzziness, to respond to a natural assumption that imaged objects are crisp, and that fuzziness is mainly due to the imaging and digitization process. The segmentation is formulated as an optimization problem and solved by the Spectral Projected Gradient method. This fast, deterministic optimization method enables practical applicability of the proposed segmentation method. Evaluation on both synthetic and real images confirms very good performance of the algorithm.
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| 8. |
- Lindblad, Joakim, et al.
(författare)
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De-noising of SRµCT Fiber Images by Total Variation Minimization
- 2010
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Ingår i: Proceedings of the 20th International Conference on Pattern Recognition (ICPR10). - Istanbul, Turkey. - 1051-4651. - 9781424475421 ; , s. 4621-4624
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Konferensbidrag (refereegranskat)abstract
- SRμCT images of paper and pulp fiber materials are characterized by a low signal to noise ratio. De-noising is therefore a common preprocessing step before segmentation into fiber and background components. We suggest a de-noising method based on total variation minimization using a modified Spectral Conjugate Gradient algorithm. Quantitative evaluation performed on synthetic 3D data and qualitative evaluation on real 3D paper fiber data confirm appropriateness of the suggested method for the particular application.
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| 9. |
- Lindblad, Joakim, et al.
(författare)
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Linear time distances between fuzzy sets with applications to pattern matching and classification
- 2014
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Ingår i: IEEE Transactions on Image Processing. - 1057-7149 .- 1941-0042. ; 23:1, s. 126-136
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Tidskriftsartikel (refereegranskat)abstract
- We present four novel point-to-set distances defined for fuzzy or gray-level image data, two based on integration over α-cuts and two based on the fuzzy distance transform. We explore their theoretical properties. Inserting the proposed point-to-set distances in existing definitions of set-to-set distances, among which are the Hausdorff distance and the sum of minimal distances, we define a number of distances between fuzzy sets. These set distances are directly applicable for comparing gray-level images or fuzzy segmented objects, but also for detecting patterns and matching parts of images. The distance measures integrate shape and intensity/membership of observed entities, providing a highly applicable tool for image processing and analysis. Performance evaluation of derived set distances in real image processing tasks is conducted and presented. It is shown that the considered distances have a number of appealing theoretical properties and exhibit very good performance in template matching and object classification for fuzzy segmented images as well as when applied directly on gray-level intensity images. Examples include recognition of hand written digits and identification of virus particles. The proposed set distances perform excellently on the MNIST digit classification task, achieving the best reported error rate for classification using only rigid body transformations and a kNN classifier.
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| 10. |
- Lindblad, Joakim, et al.
(författare)
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Optimizing optics and imaging for pattern recognition based screening tasks
- 2014
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Ingår i: Proceedings - International Conference on Pattern Recognition. - : IEEE Computer Society. - 1051-4651. - 9781479952083 ; , s. 3333-3338
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Konferensbidrag (refereegranskat)abstract
- We present a method for simulating lower quality images starting from higher quality ones, based on acquired image pairs from different optical setups. The method does not require estimates of point (or line) spread functions of the system, but utilizes the relative transfer function derived from images of real specimen of interest in the observed application. Thanks to the use of a larger number of real specimen, excellent stability and robustness of the method is achieved. The intended use is exploring the influence of image quality on features and classification accuracy in pattern recognition based screening tasks. Visual evaluation of the obtained images strongly confirms usefulness of the method. The approach is quantitatively evaluated by observing stability of feature values, proven useful for PAP-smear classification, between synthetic and real images from seven different microscope setups. The evaluation shows that features from the synthetically generated lower resolution images are as similar to features from real images at that resolution, as features from two different images of the same specimen, taken at the same low resolution, are to each other.
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| 11. |
- Lukic, Tibor, et al.
(författare)
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Regularized image denoising based on spectral gradient optimization
- 2011
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Ingår i: Inverse Problems. - : IOP Publishing. - 0266-5611 .- 1361-6420. ; 27:8, s. 085010:1-17
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Tidskriftsartikel (refereegranskat)abstract
- Image restoration methods, such as denoising, deblurring, inpainting, etc, are often based on the minimization of an appropriately defined energy function. We consider energy functions for image denoising which combine a quadratic data-fidelity term and a regularization term, where the properties of the latter are determined by a used potential function. Many potential functions are suggested for different purposes in the literature. We compare the denoising performance achieved by ten different potential functions. Several methods for efficient minimization of regularized energy functions exist. Most are only applicable to particular choices of potential functions, however. To enable a comparison of all the observed potential functions, we propose to minimize the objective function using a spectral gradient approach; spectral gradient methods put very weak restrictions on the used potential function. We present and evaluate the performance of one spectral conjugate gradient and one cyclic spectral gradient algorithm, and conclude from experiments that both are well suited for the task. We compare the performance with three total variation-based state-of-the-art methods for image denoising. From the empirical evaluation, we conclude that denoising using the Huber potential (for images degraded by higher levels of noise; signal-to-noise ratio below 10 dB) and the Geman and McClure potential (for less noisy images), in combination with the spectral conjugate gradient minimization algorithm, shows the overall best performance.
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| 12. |
- Malmberg, Filip, 1980-, et al.
(författare)
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A Graph-based Framework for Sub-pixel Image Segmentation
- 2011
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Ingår i: Theoretical Computer Science. - : Elsevier BV. - 0304-3975 .- 1879-2294. ; 412:15, s. 1338-1349
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Tidskriftsartikel (refereegranskat)abstract
- Many image segmentation methods utilize graph structures for representing images, where the flexibility and generality of the abstract structure is beneficial. By using a fuzzy object representation, i.e., allowing partial belongingness of elements to image objects, the unavoidable loss of information when representing continuous structures by finite sets is significantly reduced,enabling feature estimates with sub-pixel precision.This work presents a framework for object representation based on fuzzysegmented graphs. Interpreting the edges as one-dimensional paths betweenthe vertices of a graph, we extend the notion of a graph cut to that of a located cut, i.e., a cut with sub-edge precision. We describe a method for computing a located cut from a fuzzy segmentation of graph vertices. Further,the notion of vertex coverage segmentation is proposed as a graph theoretic equivalent to pixel coverage segmentations and a method for computing such a segmentation from a located cut is given. Utilizing the proposed framework,we demonstrate improved precision of area measurements of synthetic two-dimensional objects. We emphasize that although the experiments presented here are performed on two-dimensional images, the proposed framework is defined for general graphs and thus applicable to images of any dimension.
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| 13. |
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| 14. |
- Sladoje, Natasa, et al.
(författare)
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The coverage model and its use in image processing
- 2012
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Ingår i: Selected Topics on Image Processing and Cryptology. - Belgrade, Serbia : Mathematical Institute of the Serbian Academy of Sciences and Arts. - 9788680593470 ; , s. 39-117
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Bokkapitel (refereegranskat)
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| 15. |
- Tanács, Attila, et al.
(författare)
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Estimation of linear deformations of 3D objects
- 2010
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Ingår i: Proceedings of 2010 IEEE 17th International Conference on Image Processing. - 9781424479924 ; , s. 153-156
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Konferensbidrag (refereegranskat)abstract
- We propose a registration method to find affine transformations between 3D objects by constructing and solving an overdetermined system of polynomial equations. We utilize voxel coverage information for more precise object boundary description. An iterative solution enables us to easily adjust the method to recover e.g. rigid-body and similarity transformations. Synthetic tests show the advantage of the voxel coverage representation, and reveal the robustness properties of our method against different types of segmentation errors. The method is tested on a real medical CT volume.
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