A survey of thresholding techniques
Computer Vision, Graphics, and Image Processing
Automatic thresholding of gray-level pictures using two-dimensional entropy
Computer Vision, Graphics, and Image Processing
Maximum entropy segmentation based on the autocorrelation function of the image histogram
Journal of Computing and Information Technology
A novel fuzzy entropy approach to image enhancement and thresholding
Signal Processing
Theoretical Computer Science
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Geometric Primitive Extraction Using a Genetic Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation using evolutionary computation
IEEE Transactions on Evolutionary Computation
Genetic object recognition using combinations of views
IEEE Transactions on Evolutionary Computation
A technique of three-level thresholding based on probability partition and fuzzy 3-partition
IEEE Transactions on Fuzzy Systems
Fuzzy homogeneity approach to multilevel thresholding
IEEE Transactions on Image Processing
Thresholding using two-dimensional histogram and fuzzy entropy principle
IEEE Transactions on Image Processing
A novel fuzzy classification entropy approach to image thresholding
Pattern Recognition Letters
Object segmentation using ant colony optimization algorithm and fuzzy entropy
Pattern Recognition Letters
A novel fuzzy classification entropy approach to image thresholding
Pattern Recognition Letters
A Bayes-Based Region-Growing Algorithm for Medical Image Segmentation
Computing in Science and Engineering
Non-supervised image segmentation based on multiobjective optimization
Pattern Recognition Letters
Computer Vision and Image Understanding
The strongest schema learning GA and its application to multilevel thresholding
Image and Vision Computing
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Improving generalization of fuzzy IF-THEN rules by maximizing fuzzy entropy
IEEE Transactions on Fuzzy Systems
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Engineering Applications of Artificial Intelligence
SAR image segmentation based on Artificial Bee Colony algorithm
Applied Soft Computing
Image segmentation based on fuzzy 3-partition entropy approach and genetic algorithm
PDCAT'04 Proceedings of the 5th international conference on Parallel and Distributed Computing: applications and Technologies
An adaptive bacterial foraging algorithm for fuzzy entropy based image segmentation
Expert Systems with Applications: An International Journal
Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends
Machine Graphics & Vision International Journal
Engineering Applications of Artificial Intelligence
A modified artificial bee colony algorithm with its applications in signal processing
International Journal of Computer Applications in Technology
Expert Systems with Applications: An International Journal
A novel image thresholding method based on membrane computing and fuzzy entropy
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
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In the paper, a three-level thresholding method for image segmentation is presented, based on probability partition, fuzzy partition and entropy theory. A new fuzzy entropy has been defined through probability analysis. The image is divided into three parts, namely, dark, gray and white part, whose member functions of the fuzzy region are Z-function and Π-function and S-function, respectively, while the width and attribute of the fuzzy region can be determined by maximizing fuzzy entropy. The procedure for finding the optimal combination of all the fuzzy parameters is implemented by a genetic algorithm with appropriate coding method so as to avoid useless chromosomes. The experiment results show that the proposed method gives good performance.