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EN
Recent investigations in neuropsychology and psychology of vision have proven that human eye does not get all the information from the surrounding world in the same degree. There are three classes of signals received by human brain. The more important one is the information about features such as corners, junctions, ends of lines, etc. Straight lines and edges are the second in the hierarchy of importance. And the last ones are textures they support the less important information about objects. Basing on these results, in image processing, theory of intrinsic dimensionality and related to it theory of feature extractors have been established. In the paper a survey of approaches that are used for construction of feature extractors based on intrinsic dimensionality have been presented. To carry out experiments the approach based on geometrical wavelets has been chosen and the software prepared by the first author has been used. Experiments presented in the paper have been performed on relatively complex images that had been faces' images. They confirmed that the information about the basic elements of faces (eyes, nose, lips, etc.) might be properly extracted from the face with the usage of the feature extractor. Moreover, the experiments have shown that in this way one could obtain the smallest possible amount of information, which was enough that human eyes yet have seen the face. Very promising results of experiments suggest that it is possible to use the proposed approach to face identification and recognition. Also some possible medical applications have been suggested.
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