| 1. |
- Borgefors, Gunilla, et al.
(författare)
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Efficient shape representation by minimizing the set of centres of maximal discs/spheres
- 1997
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Ingår i: Pattern Recognition Letters. - : ELSEVIER SCIENCE BV. - 0167-8655 .- 1872-7344. ; 18:5, s. 465-471
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Tidskriftsartikel (refereegranskat)abstract
- Efficient shape representations are important for many image processing applications. Distance transform based algorithms can be used to compute the set of centres of maximal discs/spheres, that represents a shape. This paper describes a method that reduc
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| 2. |
- Johansson, Jan-Olof, 1941-
(författare)
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Measuring homogeneity of planar point-patterns by using kurtosis
- 2000
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Ingår i: Pattern Recognition Letters. - Amsterdam : Elsevier. - 0167-8655 .- 1872-7344. ; 21:13-14, s. 1149-1156
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Tidskriftsartikel (refereegranskat)abstract
- Kurtosis is generally associated with measurements of peakedness of a distribution. In this paper, we suggest a method where kurtosis can be used as a measure of homogeneity of any quantifiable property on a planar surface. A 2-dimensional, continuous and uniform distribution has kurtosis equal to 5.6. This value is also the limiting value for a discrete uniform distribution defined on a regular, rectangular grid when the number of grid points tend to infinity. Measurements of a planar surface, taken at regular grid points, are considered as realizations of random fields. These are associated with 2-dimensional random variables from which the value of kurtosis can be computed and used as a measure of the homogeneity of the field. A deviation from 5.6 indicates that the stochastic variable is not uniformly distributed and that the corresponding random field is not homogeneous. The model is applied on the spatial variation of the roughness on the surface of newsprint, an application where homogeneity is very important.
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| 3. |
- Johansson, Jan-Olof, 1941-
(författare)
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Parameter-estimation in the auto-binomial model using the coding-and pseudo-likelihood method approached with simulated annealing and numerical optimization
- 2001
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Ingår i: Pattern Recognition Letters. - Amsterdam : Elsevier. - 0167-8655 .- 1872-7344. ; 22:11, s. 1233-1246
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Tidskriftsartikel (refereegranskat)abstract
- In texture analysis, the Gibbs sampler constitutes an important tool in the generation of synthetic textures. The textures are modeled as distributions with specified parameters. In this paper, we study the estimation process of the parameters in such distributions and compare Besags coding method with a pseudo-likelihood method. We also compare simulated annealing with the Newton-Raphson method to find the global maximum of a likelihood or pseudo-likelihood function. For some textures, the two methods differ but in most case there are no important differences between them. The two maximization methods find the same maximum, but the Newton-Raphson method is much faster. However, the Newton-Raphson method cannot be applied in some cases when the location of the maximum differs too much from the starting points. Here, it is often possible to find the global maximum using simulated annealing. The methods have been used in an application with newsprint.
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| 4. |
- Kermit, M., et al.
(författare)
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Treatment of obstructive sleep apnea syndrome by monitoring patients airflow signals
- 2000
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Ingår i: Pattern Recognition Letters. - 0167-8655 .- 1872-7344. ; 21:3, s. 277-281
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Tidskriftsartikel (refereegranskat)abstract
- The breathing patterns from sleeping persons suffering from sleep apnea have been measured. A method based on the neural network-like O-algorithm has been applied to capture the onset of sleep apnea. This method is suggested as an indicator for early on-line detection of obstructions in the upper airway. Results from the system tested with airflow signals recorded from five patients during sleep indicate acceptable performance and treatment for developing apnea is possible.
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| 5. |
- Nilsson, Kenneth, 1951-, et al.
(författare)
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Localization of corresponding points in fingerprints by complex filtering
- 2003
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Ingår i: Pattern Recognition Letters. - Amsterdam : Elsevier. - 0167-8655 .- 1872-7344. ; 24:13, s. 2135-2144
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Tidskriftsartikel (refereegranskat)abstract
- For the alignment of two fingerprints certain landmark points are needed. These should be automaticaly extracted with low misidentification rate. As landmarks we suggest the prominent symmetry points (singular points, SPs) in the fingerprints. We identify an SP by its symmetry properties. SPs are extracted from the complex orientation field estimated from the global structure of the fingerprint, i.e. the overall pattern of the ridges and valleys. Complex filters, applied to the orientation field in multiple resolution scales, are used to detect the symmetry and the type of symmetry. Experimental results are reported.
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| 6. |
- Smeraldi, F., et al.
(författare)
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Retinal vision applied to facial features detection and face authentication
- 2002
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Ingår i: Pattern Recognition Letters. - Amsterdam : North-Holland Publishing. - 0167-8655 .- 1872-7344. ; 23:4, s. 463-475
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Tidskriftsartikel (refereegranskat)abstract
- Retinotopic sampling and the Gabor decomposition have a well-established role in computer vision in general as well as in face authentication. The concept of Retinal Vision we introduce aims at complementing these biologically inspired tools with models of higher-order visual process, specifically the Human Saccadic System. We discuss the Saccadic Search strategy, a general purpose attentional mechanism that identifies semantically meaningful structures in images by performing "jumps" (saccades) between relevant locations. Saccade planning relies on a priori knowledge encoded by SVM classifiers. The raw visual input is analysed by means of a log-polar retinotopic sensor, whose receptive fields consist in a vector of modified Gabor filters designed in the log-polar frequency plane. Applicability to complex cognitive tasks is demonstrated by facial landmark detection and authentication experiments over the M2VTS and Extended M2VTS (XM2VTS) databases.
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| 7. |
- Svedberg, D., et al.
(författare)
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Calibration, pose and novel views from single images of constrained scenes
- 2000
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Ingår i: Pattern Recognition Letters. - 0167-8655 .- 1872-7344. ; 21:13-14, s. 1125-1133
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Tidskriftsartikel (refereegranskat)abstract
- We exploit the common constraint of having a right-angle corner of two rectangular planes in the scene in order to calibrate a perspective projection camera and compute its pose relative to the coordinate system defined by the corner. No metric information about the corner is assumed. The camera is constrained to have its image x- and y-axes to be orthogonal with the same scale factor, which is valid for most real-world cameras. We then reproject the image of the corner to an arbitrary viewpoint. We can also compute the metric properties of the scene to scale. We report experimental results with subjectively acceptable quality. The approach shows the power of exploiting constraints that are abundant in typical architectural scenes.
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| 8. |
- Svensson, Stina, et al.
(författare)
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Curve skeletonization of surface-like objects in 3D images guided by voxel classification
- 2002
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Ingår i: Pattern Recognition Letters. - 0167-8655 .- 1872-7344. ; 23:12, s. 1419-1426
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Tidskriftsartikel (refereegranskat)abstract
- Skeletonization is a way to reduce dimensionality of digital objects. Here, we present an algorithm that computes the curve skeleton of a surface-like object in a 3D image, i.e., an object that in one of the three dimensions is at most two-voxel thick. A
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| 9. |
- Verikas, Antanas, 1951-, et al.
(författare)
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Colour image segmentation by modular neural network
- 1997
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Ingår i: Pattern Recognition Letters. - Amsterdam : Elsevier. - 0167-8655 .- 1872-7344. ; 18:2, s. 173-185
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Tidskriftsartikel (refereegranskat)abstract
- In this paper segmentation of colour images is treated as a problem of classification of colour pixels. A hierarchical modular neural network for classification of colour pixels is presented. The network combines different learning techniques, performs analysis in a rough to fine fashion and enables to obtain a high average classification speed and a low classification error. Experimentally, we have shown that the network is capable of distinguishing among the nine colour classes that occur in an image. A correct classification rate of about 98% has been obtained even for two very similar black colours.
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| 10. |
- Verikas, Antanas, et al.
(författare)
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Feature Selection with Neural Networks
- 2002
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Ingår i: Pattern Recognition Letters. - Amsterdam : Elsevier. - 0167-8655 .- 1872-7344. ; 23:11, s. 1323-1335
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Tidskriftsartikel (refereegranskat)abstract
- We present a neural network based approach for identifying salient features for classification in feedforward neural networks. Our approach involves neural network training with an augmented cross-entropy error function. The augmented error function forces the neural network to keep low derivatives of the transfer functions of neurons when learning a classification task. Such an approach reduces output sensitivity to the input changes. Feature selection is based on the reaction of the cross-validation data set classification error due to the removal of the individual features. We demonstrate the usefulness of the proposed approach on one artificial and three real-world classification problems. We compared the approach with five other feature selection methods, each of which banks on a different concept. The algorithm developed outperformed the other methods by achieving higher classification accuracy on all the problems tested.
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