Texture image recognition based on bispectrum slice and BP neural network ensembles

doi:10.1109/ICICISYS.2010.5658582

CORC > 兰州理工大学 > 兰州理工大学

	Texture image recognition based on bispectrum slice and BP neural network ensembles
	Ding, Zhengjian; Yu, Yasheng
	2010
关键词	Fault tolerance Image enhancement Image recognition Intelligent computing Intelligent systems Neural networks Tellurium compounds Textures Amplitude information Bispectrum BP neural networks Classifier design Diagonal slices Neural network ensembles Spatial relationships Texture recognition
卷号	1
DOI	10.1109/ICICISYS.2010.5658582
页码	393-395
英文摘要	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. ©2010 IEEE.
会议录	Proceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116166]
专题	兰州理工大学
作者单位	School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
推荐引用方式 GB/T 7714	Ding, Zhengjian,Yu, Yasheng. Texture image recognition based on bispectrum slice and BP neural network ensembles[C]. 见:.