We develop an evidence-combining framework for extracting locally consistent di!erential structure from curved surfaces. Existing approaches are restricted by their sequential multi-stage philosophy, since important information concerning the salient features of surfaces may be discarded as necessarily condensed information is passed from stage to stage. Furthermore, since data representations ...

This paper presents an algorithm which learns a distance metric from a data set by knowledge embedding and uses the new distance metric to solve nonlinear pattern recognition problems such a clustering. ? 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Poston, W.L., et al., A qualitative analysis of the resistive grid kernel estimator, Pattern Recognition Letters 15 (1993) 219-225. The ability to estimate a probability density function from random data has applications in discriminant analysis and pattern recognition problems. A resistive grid kernel estimator (RGKE) is described which is suitable for hardware implementation. The one-dimensio...

Feature extraction has been recognized as a useful technique for pattern recognition. Feature extraction is accomplished by constructing a mapping from the measurement space to a feature space. Often, the mapping is chosen from an arbitrarily specified parametric family by optimizing the parameters with respect to a separability criterion. In the approach described here, a scalar distance funct...

Nonlinear spatial transforms are established in feature extraction and pattern recognition. This paper describes a method for calculating the cyclic crosscorrelation with the help of generalized circular transforms. Based on the crosscorrelation property, a nonlinear translation invariant autocorrelation and a complete set of simplified translation invariants, called -spectrum, can G̃ be deduced...

This paper discusses procedures for nonlinearity detection, localisation and identification in structures from time domain vibration measurements. The detection and the localisation techniques use pattern recognition tools and are based on a dissimilarity measure between the signals coming from a linear structure and the corresponding nonlinear one. The detection procedure distinguishes between...

Commercial myoelectric prosthetic systems are based on relatively simple signal acquisition and processing. Academic research has indeed been developing powerful algorithms with promising results (e.g., pattern recognition methods and linear or non-linear transformations [1-4]), but there are still no commercial systems available using these approaches because they are not robust enough for cli...

Scale-space is an important recent concept used in image processing and pattern recognition. Traditional scale-space is generated by a linear smoothing operation. We present here a nonlinear type of smoother related to mathematical morphology which meets (modiied) \scale-space ax-ioms" and also generates a \scale-space." This scale-space is full-plane and preserves the positions of features.

The support vector machine (SVM) has been widely used in pattern recognition, regression and distribution estimation for crisp data. However, when dealing with large-scale data sets, the solution by using SVM with nonlinear kernels may be difficult to find. Under this circumstance, to develop an efficient method is necessary. Recently the reduced support vector machine (RSVM) was proposed as an...