A new algorithm for object identification by their images is proposed. It combines tolerance against imaging conditions variations proper to morphological methods for image analysis by Pyt’yev with computational simplicity of methods based on separating classes of images with hyperplane. The algorithm was tested on images taken in different illuminations and views. It can be applied to analyse microscopic image in biophysics, acoustic signals in geophysics, Earth resources using satellite data, etc.
07.05.Mh Neural networks, fuzzy logic, artificial intelligence
Department of Physics, Moscow State University, Moscow, 119991 Russia
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