Applied Maths

μLaue diffraction with a polychromatic X-ray beam can be used to measure strain fields and crystal orientations of micro crystals. The hydrostatic strain tensor can be obtained once the energy profile of the reflections is measured. However, this remains a challenge both on the time scale and reproducibility of the beam position on the sample. In this review, we present a new approach to obtain the spatial and energy profiles of Laue spots by using a pn-junction charge-coupled device, an energy-dispersive area detector providing 3D resolution of incident X-rays. The morphology and energetic structure of various Bragg peaks from a single crystalline Cu micro-cantilever used as a test system were simultaneously acquired. The method facilitates the determination of the Laue spots' energy spectra without filtering the white X-ray beam. The synchrotron experiment was performed at the BM32 beamline of ESRF using polychromatic X-rays in the energy range between 5 and 25 keV and a beam ...

Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.

A new approach to achieve sub-pixel spatial resolution in a pnCCD detector with 75 × 75 µm 2 pixel size is proposed for X-ray applications in single photon counting mode. The approach considers the energy dependence of the charge cloud created by a single photon and its split probabilities between neighboring pixels of the detector based on a rectangular model for the charge cloud density. For cases where the charge of this cloud becomes distributed over three or four pixels the center position of photon impact can be reconstructed with a precision better than 2 µm. The predicted charge cloud sizes are tested at selected X-ray fluorescence lines emitting energies between 6.4 keV and 17.4 keV and forming charge clouds with size (rms) varying between 8 µm and 10 µm respectively. The 2 µm enhanced spatial resolution of the pnCCD is verified by means of an x-ray transmission experiment throughout an optical grating.

In this work we study the response of a pnCCD by means of X-ray spectroscopy in the energy range between 6 keV and 20 keV and by Laue diffraction techniques. The analyses include measurements of characteristic detector parameters like energy resolution, count rate capability and effects of different gain settings. The limit of a single photon counting operation in white beam X-ray diffraction experiments is discussed with regard to the occurrence of pile-up events, for which the energy information about individual photons is lost. In case of monochromatic illumination the pnCCD can be used as a fast conventional CCD with a charge handling capacity (CHC) of about 300,000 electrons per pixel. If the CHC is exceeded, any surplus charge will spill to neighboring pixels perpendicular to the transfer direction due to electrostatic repulsion. The possibilities of increasing the number of storable electrons are investigated for different voltage settings by exposing a single pixel with X-rays generated by a microfocus X-ray source. The pixel binning mode is tested as an alternative approach that enables a pnCCD operation with significantly shorter readout times.

A new approach to achieve sub-pixel spatial resolution in a pnCCD detector with 75 × 75 μm2 pixel size is proposed for X-ray applications in single photon counting mode. The approach considers the energy dependence of the charge cloud created by a single photon and its split probabilities between neighboring pixels of the detector based on a rectangular model for the charge cloud density. For cases where the charge of this cloud becomes distributed over three or four pixels the center position of photon impact can be reconstructed with a precision better than 2 μm. The predicted charge cloud sizes are tested at selected X-ray fluorescence lines emitting energies between 6.4 keV and 17.4 keV and forming charge clouds with size (rms) varying between 8 μm and 10 μm respectively. The 2 μm enhanced spatial resolution of the pnCCD is verified by means of an x-ray transmission experiment throughout an optical grating.

Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.