NDLI: The image auto-focusing method based on artificial neural networks

Content Provider	IEEE Xplore Digital Library
Author	Chen Guojin Li Yongning Zhu Miaofen Wang Wanqiang
Copyright Year	2010
Description	Author affiliation: School of Mechanical Engineering, Hangzhou Dianzi University, China (Chen Guojin; Li Yongning; Wang Wanqiang) \|\| School of Management, Hangzhou Dianzi University, China (Zhu Miaofen)
Abstract	According to the image feature extraction capacity based on wavelet transformation and the nonlinear, self-adaptive and pattern recognition capacity based on artificial neural networks, the image auto-focusing method based on artificial neural networks is put forward. The wavelet components' statistics obtained by the wavelet transform are taken as the inputs of the 5 layer BP neural network model. The model identifies the image definition applying the steepest descent method of the additional momentum in a variable step to adjust the network weights. The model is first trained by 75 images from a training set, and then is tested by 102 images from a testing set. The results show that it is a very effective identification method which can obtain a higher recognition rate.
Starting Page	138
Ending Page	141
File Size	699651
Page Count	4
File Format	PDF
ISBN	9781424472284
e-ISBN	9781424472307
DOI	10.1109/CIMSA.2010.5611751
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-06
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Wavelet transforms Training Testing Wavelet analysis Pattern recognition image definition identification image processing wavelet transform artificial neural networks
Content Type	Text
Resource Type	Article

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