Automatic license plate recognition system is an image processing technology used to identify vehicles by their license plates. Such systems require the recognition of characters from the plate image. Artificial neural networks are commonly used to perform character recognition due to their high noise tolerance. Feed-Forward Neural Network (FFNN) can be used to recognize the characters from ima...

This work aims to review the basic concepts of biologically realistic neural networks when applied to visual pattern recognition. A new simple model of biologically realistic visual pattern recognition that adaptively learns by example through synaptic plasticity and changes in structure is also presented. This system uses a spiking neural network composed of integrate-and-fire neurons and Hebb...

This work proposes a new automatic target classifier, based on a combined neural networks’ system, by ISAR image processing. The novelty introduced in our work is twofold. We first present a novel automatic classification procedure, and then we discuss an improved multimedia processing of ISAR images for automatic object detection. The classifier, composed by a combination of 20 feed-forward ar...

This work is released in biometric field and has as goal, development of a full automatic fingerprint identification system using methods which have been tested in LAMOSI laboratory. Promising Results of first experiences using radial basis function neural network and support vector machine pushed us to continue the exploitation of new version of neural networks which is spike neural networks a...

We review more than two hundred applications of neural networks in image processing and discuss the present and possible future role of neural networks, especially feed-forward neural networks, Kohonen feature maps and Hopfield neural networks. The various applications are categorised into a novel two-dimensional taxonomy for image processing algorithms. One dimension specifies the type of task...

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domai...

Oil spill events are one of the major risks to marine and coastal ecosystems and, therefore, early detection is crucial for minimizing environmental contamination. have a unique appearance in satellite images created by Synthetic Aperture Radar (SAR) technology, because they byproducts oil’s influence on surface capillary, causing short gravity waves that change radar’s backscatter intensity re...

This paper reviews the application of artificial neural networks in image preprocessing. Neural networks, especially uses feed-forward neural networks, Kohonen feature maps, back-propagation neural networks, multi-layer perception neural networks and Hopfield neural networks. The various applications are categorized into a novel two-dimensional taxonomy. One dimension specifies the type of task...

The paper addresses a problem of isolated vowels recognition in patients following total laryngectomy. The visual and acoustic speech modalities were separately incorporated in the machine learning algorithms. The authors used the Mel Frequency Cepstral Coefficients as acoustic descriptors of a speech signal. A lip contour was extracted from a video signal of the speaking faces using OpenCV sof...