Intelligent image processing systems

The architecture of an intelligent image processing system (IIMS) is analyzed, and the main problems related to its practical implementation are discussed. A recent trend in image processing and analysis is borrowing from the fields of artificial intelligence, pattern recognition, and neural networks in order to make it possible to automatically extract various kinds of information from static and dynamic images. The fundamental paradigms relative to the intelligent processing of images are analyzed, particular attention is devoted: to the data fusion function which initiate the process and gives information on the actual situation with the associated uncertainties; to the hypotheses function, which takes into consideration the uncertainties in the correlated data and creates the best explanations of the fused data; to the option function, which creates various response alternatives for each hypothesis simulating the resulting effects; and to the response function, which realizes the planned actions so producing new stimuli and initializing other processing cycles