Dispersive concentrating systems based on transmission phase holograms for solar applications.

The efficiency of photovoltaic generators based on different semiconductor materials with optimized band gaps can achieve considerably higher values than those contained with single-junction solar cells. A new type of concentrating system is presented which allows high concentration and simultaneous splitting of the spectral region. This dispersive and concentrating (DISCO) system is based on volume phase transmission holograms which exhibit minimum absorption, high diffraction efficiency, and adjustable dispersion. The spectral imaging properties of volume phase transmission holograms can be optimized with respect to the requirements for solar applications.

FAZYTAN: a system for fast automated cell segmentation, cell image analysis and feature extraction based on TV-image pickup and parallel processing.

Cell location, segmentation and feature extraction of cell images are principal tasks of a high-resolution system for automated cytology. To perform these tasks with high speed, image processing algorithms and the architecture of a processor have to be optimized mutually. This has led to the development of a fast system for the evaluation of cytologic samples based on an optimized TV microscope, a host minicomputer with different peripheral array processors and digital image storages. The processors are optimized in speed for two-dimensional local operations to investigate neighborhood relations and morphology in cell images. Two-dimensional transformations of TV images (288 x 512 x 8 bit) can be carried out within 20 to 200 msec. The processors are able to realize linear filter functions (correlation, convolution) as well as nonlinear functions (median filtering). A set of measurements like area, circumference and connectivity can be derived parallely from one image in 20 msec. The system performs efficient and fast detection and segmentation of cells scanned in one TV frame within one second as well as the extraction of a large number of morphologic features within a few seconds. Based on these procedures, high-resolution analysis of several thousand cells of a sample within one minute will be possible.

Structure analysis and classification of cervical cells using a processing system based on TV.

This paper presents preliminary results of a cell classification experiment using a new approach for feature extraction. The algorithm takes into account the special requirements of a fast parallel processing system (processor-oriented algorithms). A cell image is described by several hundred features derived from the nucleus only. The most significant features with respect to classification are determined by statistical analysis. Applying principal axis transform, a new feature set is computed, reduced considerably in dimensions. The data base (1,925 cell images of Papanicolaou-stained cervical specimens) was divided into a training set (963 images) and a test set (962 images). The classification results of the test set show that the recognition rate for the two-class problem (normal, suspicious) is better than 91%, using only ten morphologic features.