International Journal of Man-Machine Studies
Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
A rule-based approach to binocular stereopsis
Analysis and interpretation of range images
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Detecting the dislocations in metal crystals from microscopic images
Pattern Recognition
Robust Contour Decomposition Using a Constant Curvature Criterion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Stereo Vision Technique Using Curve-Segments and Relaxation Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A neural matching algorithm for 3-D reconstruction from stereo pairs of linear images
Pattern Recognition Letters - Special issue on neural networks for computer vision applications
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A new learning strategy for stereo matching derived from a fuzzy clustering method
Fuzzy Sets and Systems
Active Computer Vision by Cooperative Focus and Stereo
Active Computer Vision by Cooperative Focus and Stereo
New Measurements and Corner-Guidance for Curve Matching with Probabilistic Relaxation
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Learning and Feature Selection in Stereo Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The stability problem for fuzzy bidirectional associative memories
Fuzzy Sets and Systems - Possibility theory and fuzzy logic
A New Multilevel Line-Based Stereo Vision Algorithm Based on Fuzzy Techniques
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
A Theory of Human Stereo Vision
A Theory of Human Stereo Vision
Stereovision matching through support vector machines
Pattern Recognition Letters
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Relaxation Matching Techniques-A Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Foundations of Relaxation Labeling Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Experiments with a Feature Based Stereo Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo matching using Hebbian learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The non-parametric Parzen's window in stereo vision matching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On combining support vector machines and simulated annealing in stereovision matching
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hopfield network for stereo vision correspondence
IEEE Transactions on Neural Networks
A fuzzy cognitive map approach for effect-based operations: An illustrative case
Information Sciences: an International Journal
Benchmarking main activation functions in fuzzy cognitive maps
Expert Systems with Applications: An International Journal
Structural damage detection using fuzzy cognitive maps and Hebbian learning
Applied Soft Computing
Hi-index | 0.01 |
This paper outlines a method for solving the stereovision matching problem using edge segments as the primitives. In stereovision matching the following constraints are commonly used: epipolar, similarity, smoothness, ordering and uniqueness. We propose a new matching strategy under a fuzzy context in which such constraints are mapped. The fuzzy context integrates both Fuzzy Clustering and Fuzzy Cognitive Maps. With such purpose a network of concepts (nodes) is designed, each concept represents a pair of primitives to be matched. Each concept has associated a fuzzy value which determines the degree of the correspondence. The goal is to achieve high performance in terms of correct matches. The main findings of this paper are reflected in the use of the fuzzy context that allows building the network of concepts where the matching constraints are mapped. Initially, each concept value is loaded via the Fuzzy Clustering and then updated by the Fuzzy Cognitive Maps framework. This updating is achieved through the influence of the remainder neighboring concepts until a good global matching solution is achieved. Under this fuzzy approach we gain quantitative and qualitative matching correspondences. This method works as a relaxation matching approach and its performance is illustrated by comparative analysis against some existing global matching methods.