DocumentCode
2956910
Title
Simulated annealing for hierarchical pattern detection and seismic applications
Author
Huang, Kou-Yuan ; Chou, Ying-Liang
Author_Institution
Dept. of Comput. Sci., Nat. Chian Tung Univ., Hsinchu
fYear
2008
fDate
1-8 June 2008
Firstpage
1257
Lastpage
1264
Abstract
A hierarchical system is proposed by using simulated annealing for the detection of lines, circles, ellipses, and hyperbolas in image. The hierarchical detection procedures are type by type and pattern by pattern. The equation of ellipse and hyperbola is defined under translation and rotation. The distance from all points to all patterns is defined as the error. Also we use the minimum error to determine the number of patterns. The proposed simulated annealing parameter detection system can search a set of parameter vectors for the global minimal error. In the experiments, using the hierarchical system, the result of the detection of a large number of simulated image patterns is better than that of using the synchronous system. In the seismic experiments, both of two systems can well detect line of direct wave and hyperbola of reflection wave in the simulated one-shot seismogram and the real seismic data, but the hierarchical system can converge faster. The results of seismic pattern detection can improve seismic interpretation and further seismic data processing.
Keywords
geophysical signal processing; seismology; simulated annealing; global minimal error; hierarchical pattern detection; image hyperbola; parameter vectors; reflection wave hyperbola; seismic applications; seismic data processing; seismic pattern detection; simulated annealing parameter detection system; Neural networks; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4633960
Filename
4633960
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