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22 March 1999 Feature extraction from photographic images using a hybrid neural network
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Proceedings Volume 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343053
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden
Abstract
A new method for extracting features from photographic images has been developed. The input image is through a pulse coupled neural network transformed to a set of signatures, well suited for classification by unsupervised neural networks. A strategy using multiple self-organizing feature maps in a hierarchical manner is developed. With this approach, using a certain degree of supervision, an acceptable classification is obtained when applied to test images. The method is applied to license plate recognition.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vlatko Becanovic, Martin Kermit, and Age J. Eide "Feature extraction from photographic images using a hybrid neural network", Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); https://doi.org/10.1117/12.343053
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