Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed implementations of different versions of LDA, suitable ...
Sergio Valcarcel Macua, Pavle Belanovic, Santiago ...
A feature extraction method using the chaincode representation of fingerprint ridge contours is presented. The representation allows efficient image quality enhancement and detect...
In order to characterize the non-Gaussian information contained within the EEG signals, a new feature extraction method based on bispectrum is proposed and applied to the classifi...
In this paper, we present a holistic system for the recognition of cursive handwriting that utilizes a novel feature extraction method and a neural network. The Hough transform is...
This paper proposes a method for sign language recognition that bypasses the need for tracking by classifying the motion directly. The method uses the natural extension of haar li...
When recognizing multiple fonts, geometric features, such as the directional information of strokes, are generally robust against deformation but are weak against degradation. Thi...
Previous emotion recognition systems have mainly focused on pattern classification, rather than utilizing sensing technologies or feature extraction methods. This paper introduces ...
We describe a method for indexing and retrieving high-resolution image regions in large geospatial data libraries. An automated feature extraction method is used that generates a u...
Kenneth W. Tobin, Budhendra L. Bhaduri, Eddie A. B...
It is known that no single descriptor is powerful enough to encompass all aspects of image content, i.e. each feature extraction method has its own view of the image content. A pos...
Lin Mei, Gerd Brunner, Lokesh Setia, Hans Burkhard...
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...