DocumentCode :
536115
Title :
Application of an Improved Hybrid Strategy Combining RTS with EBP in the Image Segmentation of Test Strip
Author :
Wang, Jiajia ; Chen, Xiaozhu ; Tan, Jin ; Wang, Yaqun
Author_Institution :
Dept. of Comput. Sci. & Technol., China Jiliang Univ., Hangzhou, China
Volume :
1
fYear :
2010
fDate :
23-24 Oct. 2010
Firstpage :
301
Lastpage :
305
Abstract :
In this paper, a type of improved hybrid strategy is used to carry out the image segmentation of gold immuno chromato graphic test strip, which combines the reactive tabu search (RTS) algorithm and error back propagation (EBP) neural network. This hybrid strategy can solve the problems which exist in image segmentation of test strip: the area of test strip is pretty small; the breadth of test line testing zone, control line testing zone will not be fixed due to the reaction process between specimen and test strip. The results of experiment show that this hybrid strategy can improve the convergence precision and training speed of the EBP neural network. Furthermore, comparing with EBP neural network, the convergence precision and convergence speed of RTS algorithm are much better. At the end of this paper, this hybrid strategy is applied in the image segmentation of test strip and gets satisfactory effect.
Keywords :
backpropagation; biology computing; chromatography; image segmentation; neural nets; search problems; control line testing zone; error back propagation neural network; gold immunochromatographic test strip; image segmentation; reactive tabu search algorithm; test line testing zone; Artificial neural networks; Image segmentation; Neurons; Pixel; Strips; Testing; Training; EBP neutral network; gold immunochromatographic test strip; image segmentation; reactive tabu search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
Type :
conf
DOI :
10.1109/AICI.2010.70
Filename :
5656614
Link To Document :
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