The image auto-focusing method based on artificial neural networks

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' st...

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Bibliographic Details
Published in2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications pp. 138 - 141
Main Authors Chen Guojin, Li Yongning, Zhu Miaofen, Wang Wanqiang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2010
Subjects
Artificial neural networks
image definition identification
image processing
Pattern recognition
Testing
Training
Wavelet analysis
wavelet transform
Wavelet transforms
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Summary: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.
ISBN:9781424472284
1424472288
ISSN:2159-1547
2159-1555
DOI:10.1109/CIMSA.2010.5611751