A Spatial Thresholding Method for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Computer Vision
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A memetic model of evolutionary PSO for computational finance applications
Expert Systems with Applications: An International Journal
An enhanced memetic differential evolution in filter design for defect detection in paper production
Evolutionary Computation
An evolutionary memetic algorithm for rule extraction
Expert Systems with Applications: An International Journal
A probabilistic memetic framework
IEEE Transactions on Evolutionary Computation
Medical image segmentation using genetic algorithms
IEEE Transactions on Information Technology in Biomedicine
An evolutionary algorithm for discrete tomography
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
Evolutionary multi-objective optimization in robot soccer system for education
IEEE Computational Intelligence Magazine
IEEE Computational Intelligence Magazine
Density-sensitive evolutionary clustering
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Discrete tomography reconstruction through a new memetic algorithm
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
A memetic algorithm for binary image reconstruction
IWCIA'08 Proceedings of the 12th international conference on Combinatorial image analysis
Tiny GAs for image processing applications
IEEE Computational Intelligence Magazine
Image segmentation using evolutionary computation
IEEE Transactions on Evolutionary Computation
Clustering with a genetically optimized approach
IEEE Transactions on Evolutionary Computation
A study of the Lamarckian evolution of recurrent neural networks
IEEE Transactions on Evolutionary Computation
Microgenetic algorithms as generalized hill-climbing operators forGA optimization
IEEE Transactions on Evolutionary Computation
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Memetic Algorithm for VLSI Floorplanning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
A cellular coevolutionary algorithm for image segmentation
IEEE Transactions on Image Processing
Markovian approach using several Gibbs energy for remote sensing images segmentation
Analog Integrated Circuits and Signal Processing
Evolution-enhanced multiscale overcomplete dictionaries learning for image denoising
Engineering Applications of Artificial Intelligence
An improved generalized fuzzy c-means clustering algorithm based on GA
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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In order to solve the image segmentation problem which assigns a label to every Pixel in an image such that pixels with the same label share certain visual characteristics More effectively, a novel approach based on memetic algorithm (MISA) is proposed water-shed segmentation is applied to segment original images into non-overlap small regions Before performing the portioning process by MISA. MISA adopts a straightforward representation Method to find the optimal combination of watershed regions under the criteria Of interclass variance in feature space. After implementing cluster-based crossover and Mutation, an individual learning procedure moves exocentric regions in current cluster To the one they should belong to according to the distance between these regions and Cluster centers in feature space. In order to evaluate the new algorithm, six texture Images, three remote sensing images and three natural images are employed in experiments. The experimental results show that MISA outperforms its genetic version, the Fuzzy c-means algorithm and K-means algorithm in partitioning most of the test Problems, and is an effective approach when compared with two state-of-the-art Image segmentation algorithms including an efficient graph-based algorithm and a Spectral clustering ensemble-based algorithm.