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The image auto-focusing method based on artificial neural networks

机译:基于人工神经网络的图像自动聚焦方法

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摘要

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.
机译:针对基于小波变换的图像特征提取能力以及基于人工神经网络的非线性,自适应和模式识别能力,提出了基于人工神经网络的图像自动聚焦方法。通过小波变换获得的小波分量统计量作为5层BP神经网络模型的输入。该模型使用可变动量的附加动量的最速下降方法来识别图像清晰度,以调整网络权重。首先通过训练集中的75张图像对模型进行训练,然后通过测试集中的102张图像对模型进行测试。结果表明,它是一种非常有效的识别方法,可以获得较高的识别率。

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