Two-dimensional gel electrophoresis is a powerful tool for determining the protein content of biological samples. At present, however, the great quantity of data to be extracted and examined does not allow its application on a wide scale; this result will be attained through the automation of the entire process. In this paper we analyze some basic problems involved in the automated analysis of electrophoresis images, propose some new solutions, and discuss the results obtained in experimental situations. In particular, spatial resolution is discussed, utilizing the results of spot-detection and segmentation procedures applied to images of three different resolutions. A spot-detection method based on the zero crossing of the first derivative of spot density is proposed. Spot segmentation is performed by testing the signs of second-order incremental ratios of spot density. Overlapped spots are separated by iteratively estimating the isolated spot densities, under the assumptions of density additivity and spot symmetry. Pattern recognition for feature extraction and cluster analysis for detection of spot gel constellations are proposed. Finally, an optical-flow calculation technique is modified for application to gel matching. The results obtained by means of such methodologies are promising and could be utilized by a knowledge-based system for automatic interpretation of electrophoresis images; this is the objective we propose for future research in this field.