Feature extraction from photographic images using a hybrid neural network

Vlatko Becanovic; Martin Kermit; Age J. Eide

doi:10.1117/12.343053

22 March 1999 Feature extraction from photographic images using a hybrid neural network

Vlatko Becanovic, Martin Kermit, Age J. Eide

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.

Citation Download Citation

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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