A new fuzzy relaxation algorithm for image enhancement
International Journal of Knowledge-based and Intelligent Engineering Systems
EURASIP Journal on Applied Signal Processing
A novel approach to neuro-fuzzy classification
Neural Networks
Centroid Neural Network with Spatial Constraints
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Video sequence motion tracking by fuzzification techniques
Applied Soft Computing
DS '09 Proceedings of the 12th International Conference on Discovery Science
A weight-featured and data-distribution-based fuzzy pattern classification approach
Control and Intelligent Systems
Pattern Recognition Letters
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Classification and segmentation of brain tumor using texture analysis
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Multilevel image segmentation with adaptive image context based thresholding
Applied Soft Computing
Engineering Applications of Artificial Intelligence
Adaptive interference signal processing with intelligent neuro-fuzzy approach
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Automated computational delimitation of SST upwelling areas using fuzzy clustering
Computers & Geosciences
Knowledge discovery by an intelligent approach using complex fuzzy sets
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Generating fuzzy edge images from gradient magnitudes
Computer Vision and Image Understanding
Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends
Machine Graphics & Vision International Journal
A new gravitational image edge detection method using edge explorer agents
Natural Computing: an international journal
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An autoadaptive neuro-fuzzy segmentation and edge detection architecture is presented. The system consists of a multilayer perceptron (MLP)-like network that performs image segmentation by adaptive thresholding of the input image using labels automatically pre-selected by a fuzzy clustering technique. The proposed architecture is feedforward, but unlike the conventional MLP the learning is unsupervised. The output status of the network is described as a fuzzy set. Fuzzy entropy is used as a measure of the error of the segmentation system as well as a criterion for determining potential edge pixels. The proposed system is capable to perform automatic multilevel segmentation of images, based solely on information contained by the image itself. No a priori assumptions whatsoever are made about the image (type, features, contents, stochastic model, etc.). Such an "universal" algorithm is most useful for applications that are supposed to work with different (and possibly initially unknown) types of images. The proposed system can be readily employed, "as is," or as a basic building block by a more sophisticated and/or application-specific image segmentation algorithm. By monitoring the fuzzy entropy relaxation process, the system is able to detect edge pixels