A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A GP Artificial Ant for Image Processing: Preliminary Experiments with EASEA
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
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
Morphological algorithm design for binary images using genetic programming
Genetic Programming and Evolvable Machines
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
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 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
Gaussian-based edge-detection methods-a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Edge detection in untextured and textured images-a common computational framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
Genetic programming for edge detection based on figure of merit
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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Gaussian-based edge detectors have been developed for many years, but there are still problems with how to set scales for Gaussian filters and how to combine Gaussian filters. In order to address both problems, a Genetic Programming (GP) system is proposed to automatically choose scales for Gaussian filters and automatically combine Gaussian filters. In this study, the GP system is utilised to construct rotation invariant Gaussian-based edge detectors based on a benchmark image dataset. The experimental results show that the GP evolved Gaussian-based edge detectors are better than the Gaussian gradient and rotation invariant surround suppression to extract edge features.