Geert M. P. van Kempen

Learn 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)
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)
Application of image restoration methods for confocal fluorescence microscopy, in: C. ABSTRACT 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(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 segmenta-tion which is(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)
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)
The restoration of images acquired by a fluorescence microscope is in the presence of noise known to be a difficult problem. This presence of noise can result in restored images that contain severe noise artifacts, or that are smoothed by a strongly imposed regularization. In both cases, small textures present in the image, are lost in the restoration(More)
To segment multi-spectral images new methods are required which operate both in spectral and spatial domains and work with a high-dimensional data. We are presenting a new segmentation method that is built from standard statistical pattern recognition algorithms. It integrates spectral and spatial domain information by a combined classifier approach. We(More)