Acta Photonica Sinica, Volume. 40, Issue 7, 1066(2011)
SWBF Classification Based on BP Neural Network
A new method which classification of simulated wake bubble films(SWBF)can be obtained by using imaging processing methods. The paper introducts the basic structure and working principals of the BP neural network, the simulation tested classification of SWBF image based on BP neural network. The characteristic quantities such as mean value,normalized coefficient,the third moment,uniformity, entropy can be extracted based on gray histogram statistical moment. After 14 epochs, training error can be reached 0.001 when we setting neural network learning rate is 0.1, while the classification accuracy can be up to 100% under different pressures on SWBF.The method has characteristics such as visibility, high efficiency and accuracy, and can be apt to applied in engineering projects for wakes′ detection and recognition.
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CHANG Yang, CUI Hong, ZHANG Jiansheng. SWBF Classification Based on BP Neural Network[J]. Acta Photonica Sinica, 2011, 40(7): 1066
Received: Nov. 8, 2010
Accepted: --
Published Online: Aug. 10, 2011
The Author Email: Yang CHANG (rogerfederer@126.com)