Intelligent visual recognition and classification of cork tiles with neural networks

Authors:
Antoniya Georgieva;Ivan Jordanov
Affiliations:
Nuffield Department of Obstetrics and Gynecology, University of Oxford, Oxford, UK;School of Computing, University of Portsmouth, Portsmouth, UK
Venue:
IEEE Transactions on Neural Networks
Year:
2009

Citing 12
Cited 5

Filtering for Texture Classification: A Comparative Study

IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Pattern Recognition: A Review

IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition

Neural Networks for Pattern Recognition
Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy

IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision: Theory, Algorithms, Practicalities

Machine Vision: Theory, Algorithms, Practicalities
A Linear Feature Extraction for Multiclass Classification Problems Based on Class Mean and Covariance Discriminant Information

IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition, Third Edition

Pattern Recognition, Third Edition
Automatic texture feature selection for image pixel classification

Pattern Recognition
Evolutionary discriminant analysis

IEEE Transactions on Evolutionary Computation
Cork quality classification system using a unified image processing and fuzzy-neural network methodology

IEEE Transactions on Neural Networks
A Pyramidal Neural Network For Visual Pattern Recognition

IEEE Transactions on Neural Networks
Neural Network Learning With Global Heuristic Search

IEEE Transactions on Neural Networks

Intelligent hybrid system for pattern recognition and classification

CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Fabric defect classification using radial basis function network

Pattern Recognition Letters
A parallel evolving algorithm for flexible neural tree

Parallel Computing
Object recognition using a bio-inspired neuron model with bottom-up and top-down pathways

Neurocomputing
Swarm optimization and Flexible Neural Tree for microarray data classification

Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

An intelligent machine vision system is investigated and used for pattern recognition and classification of seven different types of cork tiles. The system includes image acquisition with a charge-coupled device (CCD) camera, texture feature generation (co-occurrence matrices and Laws' masks), analysis and processing of the feature vectors [linear discriminant analysis (LDA) and principal component analysis (PCA)], and cork tiles classification with feedforward neural networks (NN), employing our GLPτS (genetic low-discrepancy search) hybrid global optimization method. In addition, the same NN are trained with backpropagation (BP) and the obtained results are compared with the ones from GLPτS. The NN generalization abilities are discussed and assessed with respect to the NN architectures and the texture feature sets. The reported results are very encouraging with testing rate reaching up to 95%.