Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A review of recent texture segmentation and feature extraction techniques
CVGIP: Image Understanding
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Unsupervised texture segmentation of images using tuned matched Gabor filters
IEEE Transactions on Image Processing
Optimal Gabor filters for texture segmentation
IEEE Transactions on Image Processing
Extracting rules for classification problems: AIS based approach
Expert Systems with Applications: An International Journal
A hybrid feature selection approach based on the Bayesian network classifier and rough sets
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
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This paper introduces a novel method to detect texture objects from satellite images. First, a hierarchical strategy is developed to extract texture objects according to their roughness. Then, an artificial immune approach is presented to automatically generate segmentation thresholds and texture filters, which are used in the hierarchical strategy. In this approach, texture objects are regarded as antigens, and texture object filters and segmentation thresholds are regarded as antibodies. The clonal selection algorithm inspired by human immune system is employed to evolve antibodies. The population of antibodies is iteratively evaluated according to a statistical performance index corresponding to object detection ability, and evolves into the optimal antibody using the evolution principles of the clonal selection. Experimental results of texture object detection on satellite images are presented to illustrate the merit and feasibility of the proposed method.