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