DocumentCode :
536277
Title :
Texture image recognition based on bispectrum slice and BP neural network ensembles
Author :
Ding, Zhengjian ; Yu, Yasheng
Author_Institution :
Sch. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
Volume :
1
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
393
Lastpage :
395
Abstract :
To obtain the spatial relationship between three or more pixels in the texture image, bispectrum is choosen to extract texture features of the image, and it contains amplitude information and phase information of the image. Due to some problems in neural network, such as unstable classifier design, configuration, training, the research based on the ensemble of neural networks appears. Compared with a single neural network, an ensemble of neural networks has better fault tolerance and generalisation ability. In this paper, bispectrum is used to extract texture features and the neural network ensembles are used to recognize the texture images. The experimental results demonstrate that the ensemble of BP neural networks can effectively improve correct recognition rate of texture images.
Keywords :
backpropagation; feature extraction; image recognition; image texture; neural nets; BP neural network ensembles; amplitude information; bispectrum slice; fault tolerance; phase information; spatial relationship; texture feature extraction; texture image recognition; Instruction sets; Bispectrum; diagonal slice; neural network ensembles; texture recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658582
Filename :
5658582
Link To Document :
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