A multi-objective memetic algorithm for intelligent feature extraction

Authors:
Paulo V. W. Radtke;Tony Wong;Robert Sabourin
Affiliations:
Department de Génie de la Production Automatisé, École de Technologie Supérieure, Laboratoire d'Imagerie, de Vision et d'Intelligence Artificielle, Montréal, QC, C ...;Department de Génie de la Production Automatisé, École de Technologie Supérieure, Laboratoire d'Imagerie, de Vision et d'Intelligence Artificielle, Montréal, QC, C ...;Department de Génie de la Production Automatisé, École de Technologie Supérieure, Laboratoire d'Imagerie, de Vision et d'Intelligence Artificielle, Montréal, QC, C ...
Venue:
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Year:
2005

Citing 11
Cited 2

Off-Line Signature Verification by Local Granulometric Size Distributions

IEEE Transactions on Pattern Analysis and Machine Intelligence
A structural/statistical feature based vector for handwritten character recognition

Pattern Recognition Letters
The partition-combination method for recognition of handwritten characters

Pattern Recognition Letters
Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study

PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Feature Subset Selection Using Genetic Algorithms for Handwritten Digit Recognition

SIBGRAPI '01 Proceedings of the 14th Brazilian Symposium on Computer Graphics and Image Processing
Handwritten Numerical Recognition Using Autoassociative Neural Networks

ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit Recognition

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Intelligent Zoning Design Using Multi-Objective Evolutionary Algorithms

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Do multiple-objective metaheuristics deliver on their promises? A computational experiment on the set-covering problem

IEEE Transactions on Evolutionary Computation
Solving the traveling salesman problem with annealing-based heuristics: a computational study

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Intelligent Feature Extraction for Ensemble of Classifiers

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Zoning methods for handwritten character recognition: A survey

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a methodology to generate representations for isolated handwritten symbols, modeled as a multi-objective optimization problem. We detail the methodology, coding domain knowledge into a genetic based representation. With the help of a model on the domain of handwritten digits, we verify the problematic issues and propose a hybrid optimization algorithm, adapted to needs of this problem. A set of tests validates the optimization algorithm and parameter settings in the model's context. The results are encouraging, as the optimized solutions outperform the human expert approach on a known problem.