Geert M. P. van Kempen

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The analysis of the three-dimensional structure of tissue, cells and cellular constituents play a major role in biomedical research. Three-dimensional images, acquired by confocal fluorescence microscopes play a key role in this analysis. However, the imaging properties of these microscopes give rise to diffraction-induced blurring phenomena. These(More)
Dit proefschrift is goedgekeurd door de promotor(en): This work was carried out in graduate school ASCI. ASCI dissertation series number 39. This thesis presents image restoration techniques for applications in (confocal) fluorescence microscopy. We have gained a better understanding of the behavior of non-linear image restoration algorithms and we have(More)
Cereal Chem. 80(4):390–395 The structure of bread crumb is an important factor in consumer acceptance of bakery products. The noninvasive monitoring of the gas cell formation during the proofing of dough can aid in understanding the mechanisms governing the crumb appearance in the baked product. The development of gas cells during the proofing of dough was(More)
This paper reports studies on the influence of the regularization parameter and the first estimate on the performance of iterative image restoration algorithms. We discuss regularization parameter estimation methods that have been developed for the linear Tikhonov–Miller filter to restore images distorted by additive Gaussian noise. We have performed(More)
We present the application of a local dimensionality estimator to the analysis of 3-D microscopic network structures. Three-dimensional images of these structures have been acquired with a fluorescence confocal microscope. We derive the smoothed gradient square tensor (GST) in 3D and show how the eigenvalues and eigenvectors of the tensor can be computed(More)
Feature selection is an important tool reducing necessary feature acquisition time in some applications. Standard methods, proposed in the literature, do not cope with the measurement cost issue. Including the measurement cost into the feature selection process is difficult when features are grouped together due to the implementation. If one feature from a(More)
A quantitative comparison of two restoration methods as applied to confocal microscopy, Proc. 1. Introduction The main contribution of the confocal microscope to microscopy is that it provides a practical method to obtain microscopic volume images. Although a confocal microscope is a true volume imager, its imaging properties give rise to a blurring(More)
Morphological sieves are capable of classifying objects in images according to their size. They yield a granulometry, which describes the imaged structure. The discrete sieve has some disadvantages that its continuous-domain counterpart does not have: sampled disks (used as isotropic structuring elements) are rather anisotropic, especially at small scales,(More)
Segmentation methods, combining spectral and spatial information, are essential for analysis of multi-spectral images. In this article, we propose such a method based on statistical pattern recognition algorithms and a combined classifier approach. A set of experiments is presented with multi-spectral images of detergent laundry powders acquired by imaging(More)
In this paper we present an application of statistical pattern recognition for segmentation of backscatter images (BSE) in product analysis of laundry detergents. Currently, application experts segment BSE images interactively which is both time consuming and expert dependent. We present a new, automatic, procedure for supervised BSE segmentation which is(More)