Digital Picture Analysis In Microphotometry Of Biological Materials

Abstract

Automatic evaluation of two-dimensional thin-layer-chromatograms exemplarily demonstrates the applicability of signal processing, image analysis, and pattern recognition to microphotometry by an enlarged dynamic range of the photometer, improved reproducibility by noise reduction, discrimination between objects and background, feature extraction and automatic classification of the results. Emphasis is put on simple procedures which are tested in routine work and can be implemented on minicomputers.