A new method of parameters determined in image recognition by PCNN

S. He, Dianhong Wang
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引用次数: 1

Abstract

The aim of this paper is to research the image recognition system and its applications, which is based on combining the traditional BP neural networks and the third-generation pulse coupled neural network (PCNN).The process is by extracting the image's time and entropy sequences, then through the fast Fourier transform, and finally as inputs of the pattern classification. In order to test the stability of the system, we make some varies by rotating, tension and compressing the original image, meanwhile, combined with the statistics of the entropy information to determine the time delay parameter of the pcnn, the recognition results is satisfactory.
一种新的PCNN图像识别参数确定方法
本文的目的是研究基于传统BP神经网络与第三代脉冲耦合神经网络(PCNN)相结合的图像识别系统及其应用。该过程是通过提取图像的时间和熵序列,然后通过快速傅立叶变换,最后作为模式分类的输入。为了测试系统的稳定性,我们通过旋转、拉伸和压缩原始图像来进行一些变化,同时结合熵信息的统计来确定pcnn的时滞参数,识别结果令人满意。
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