Pii: S0031-3203(97)00089-7

Optimizing the cost matrix for approximate string matching using genetic algorithms

Model-based Bayesian feature matching with application to synthetic aperture radar target recognition

We present a Bayesian approach for model-based classi"cation from unordered, attributed feature sets. A set of features is estimated from measured data and is matched with a set predicted for each candidate hypothesis using a feature model. Both extracted and predicted feature sets have uncertainty, and some features may not be present in one set or the other. Computation of the match likelihoo...

Adaptive skin color modeling using the skin locus for selecting training pixels

Techniques for color-based tracking of faces or hands often assume a static skin model yet skin color, as measured by a camera, can change when lighting changes. Therefore, for robust skin pixel detection, an adaptive skin color model must be employed. We demonstrate a chromaticity-based constraint to select training pixels in a scene for updating a dynamic skin color model under changing illum...

Pii: S0031-3203(01)00129-7

This paper presents a survey on o!-line Cursive Word Recognition. The approaches to the problem are described in detail. Each step of the process leading from raw data to the /nal result is analyzed. This survey is divided into two parts, the /rst one dealing with the general aspects of Cursive Word Recognition, the second one focusing on the applications presented in the literature. ? 2002 Pat...

Relaxation labeling using augmented lagrange-hopfield method

A novel relaxation labeling (RL) method is presented based on Augmented Lagrangian multipliers and the graded Hoppeld neural network (ALH). In this method, an RL problem is converted into a constrained optimization problem and solved by using the augmented Lagrangian and Hoppeld techniques. The ALH method yields results comparable to the best of the existing RL algorithms in terms of the optimi...