An Image Recognition Method Based on Wavelet Packet and GA-BP Neural Network

BAI Tie-cheng; ZHANG Ren; QI Li-mei; REN Bin

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An Image Recognition Method Based on Wavelet Packet and GA-BP Neural Network

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- An Image Recognition Method Based on Wavelet Packet and GA-BP Neural Network
- Vol. 16, Issue 6, Pages: 68-72(2011)
- 作者机构：
  
  1. 塔里木大学信息工程学院
  2. 哈尔滨理工大学测控技术与通信工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： S436.65;TP183
- Published：2011
- 稿件说明：
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BAI Tie-cheng, ZHANG Ren, QI Li-mei, et al. An Image Recognition Method Based on Wavelet Packet and GA-BP Neural Network[J]. 2011, 16(6): 68-72.
DOI：

BAI Tie-cheng, ZHANG Ren, QI Li-mei, et al. An Image Recognition Method Based on Wavelet Packet and GA-BP Neural Network[J]. 2011, 16(6): 68-72. DOI：

摘要

针对传统人工枣树病害识别费时费力的问题

提出了一种小波包和GA-BP神经网络结合的快速识别方法.通过小波包去噪方法

消除病害图像采集过程中随机噪声产生的干扰

采用小波包分解系数矩阵的奇异值和小波包变换模极大值矩阵的奇异值构造特征输入参数

利用遗传算法优化后的BP神经网络建立红枣病害的识别模型.实验表明

小波包、遗传算法和神经网络相结合可以实现对红枣病害的准确、快速识别

优化后的模型识别误差达到97%

建模时间降为原来的1/9.

Abstract

A fast method based on wavelet packet and GA-BP neural network was proposed according to the traditional method of estimating red jujube disease which were slow and arduous.Firstly

a wavelet packet image processing method was used to remove the interference caused by random noise produced during the image acquisition process

and then the singular value of the wavelet packet decomposition coefficient matrix and the wavelet packet transform modulus maxima matrix was used to construct the character...

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