Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Handbook of pattern recognition & computer vision
Learning Texture Discrimination Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering methods for texture discrimination
Pattern Recognition Letters
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming for Feature Discovery and Image Discrimination
Proceedings of the 5th International Conference on Genetic Algorithms
Towards Genetic Programming for Texture Classification
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Hyperspectral Image Analysis Using Genetic Programming
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Palantír: raising awareness among configuration management workspaces
Proceedings of the 25th International Conference on Software Engineering
PADO: Learning Tree Structured Algorithms for Orchestration into an Object Recognition System
PADO: Learning Tree Structured Algorithms for Orchestration into an Object Recognition System
Adaptive Gray Level Run Length Features from Class Distance Matrices
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Synthesis of interest point detectors through genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Breast cancer diagnosis using genetic programming generated feature
Pattern Recognition
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
A hybrid image restoration approach: Using fuzzy punctual kriging and genetic programming
International Journal of Imaging Systems and Technology
Genetic programming for image analysis
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Genetic programming classification of magnetic resonance data
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Hyperspectral image analysis using genetic programming
Applied Soft Computing
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
An implicit context representation for evolving image processing filters
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Comparison of texture features based on Gabor filters
IEEE Transactions on Image Processing
Texture Detection Using Neural Networks Trained on Examples of One Class
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Interest point detection through multiobjective genetic programming
Applied Soft Computing
Evolving estimators of the pointwise Hölder exponent with Genetic Programming
Information Sciences: an International Journal
The unconstrained automated generation of cell image features for medical diagnosis
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Two-Tier genetic programming: towards raw pixel-based image classification
Expert Systems with Applications: An International Journal
Evolving event detectors in multi-channel sensor data
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Networks of transform-based evolvable features for object recognition
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Genetic programming as strategy for learning image descriptor operators
Intelligent Data Analysis
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This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.