A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Thinning Methodologies-A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing and Tracking Human Action
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
A GP Artificial Ant for Image Processing: Preliminary Experiments with EASEA
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Supervised Learning of Edges and Object Boundaries
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
GMAI '07 Proceedings of the Geometric Modelling and Imaging
Evolution of a local boundary detector for natural images via genetic programming and texture cues
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolving edge detectors with genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Genetic programming for image analysis
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Genetic programming on GPUs for image processing
International Journal of High Performance Systems Architecture
A new methodology for evaluation of edge detectors
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A novel genetic programming based morphological image analysis algorithm
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Genetic programming for edge detection based on accuracy of each training image
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Gaussian-based edge-detection methods-a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
The combination of local features in edge detection can generally improve detection performance. However, how to effectively combine different basic features remains an open issue and needs to be investigated. Multivariate density is a generalisation of the one-dimensional (univariate) distribution to higher dimensions. In order to effectively construct composite features with multivariate density, a Genetic Programming (GP) system is proposed to evolve Bayesian-based programs. An evolved Bayesian-based program estimates the relevant multivariate density to construct a composite feature. The results of the experiments show that the GP system constructs high-level combined features which substantially improve the detection performance.