nahavandi-theroughsetsfeature-2003.pdf (426.62 kB)
The rough sets feature selection for trees recognition in color aerial images using genetic algorithms
conference contribution
posted on 2003-01-01, 00:00 authored by L Pan, Saeid Nahavandi, H ZhengSelecting a set of features which is optimal for a given task is the problem which plays an important role in a wide variety of contexts including pattern recognition, images understanding and machine learning. The concept of reduction of the decision table based on the rough set is very useful for feature selection. In this paper, a genetic algorithm based approach is presented to search the relative reduct decision table of the rough set. This approach has the ability to accommodate multiple criteria such as accuracy and cost of classification into the feature selection process and finds the effective feature subset for texture classification . On the basis of the effective feature subset selected, this paper presents a method to extract the objects which are higher than their surroundings, such as trees or forest, in the color aerial images. The experiments results show that the feature subset selected and the method of the object extraction presented in this paper are practical and effective.
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Title of proceedings
Program & abstracts : the Second International Conference on Computational Intelligence, Robotics and Autonomous Systems : CIRAS 2003 : 15-18 December 2003, Pan Pacific Hotel, SingaporeEvent
International Conference on Computational Intelligence, Robotics and Autonomous Systems (2nd : 2003 : Singapore)Publisher
Center for Intelligent Control, National University of SingaporeLocation
SingaporePlace of publication
SingaporeStart date
2003-12-15End date
2003-12-18ISSN
0219-6131Language
engNotes
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E1 Full written paper - refereedCopyright notice
2003, CIRASEditor/Contributor(s)
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