Abstract
A new construction method of bi-directional associative memory (BAM) for image pattern/object recognition is proposed in this paper. The strategy of the method is based on combining the major information of each object from both spatial domain and frequency domain images. The BAM model is reconstructed by input object features and the input object's Fourier spectrum. After the BAM reconstruction, each similar input pattern can be retrieved or recognized using the two-layer neural network automatically. The presented reconstruction method allows any new input object to be stored and added into the original BAM model without extra training procedure. Experimental results indicate that the system performs good recognition ability for input object with noise. The method also provides a distortion correction way for the deformed objects. The system has been implemented in a PC- based computer.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Published Version
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