Purity identification of maize seed based on discrete wavelet transform and BP neural network

被引：0
作者：
Cao, Weishi [1 ]
Zhang, Chunqing [2 ]
Wang, Jinxing [3 ]
Liu, Shuangxi [3 ]
Xu, Xingzhen [1 ]
机构：
[1] Shandong Provincial Key Laboratory of Horticultural Machineries and Equipments
[2] College of Agricultural, Shandong Agricultural University
[3] College of Mechanical and Electronic Engineering, Shandong Agricultural University
来源：
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | 2012年 / 28卷 / SUPPL. 2期
关键词：
Color; Discrete wavelet transform; Image recognition; Maize; Neural network; Purity;
D O I：
10.3969/j.issn.1002-6819.2012.z2.044
中图分类号：
学科分类号：
摘要：
In order to identify the maize seed purity efficiently, after researching on image processing methods and classification algorithm in terms of the image characteristic of maize seed, a purity identification calculation based on discrete wavelet transform(DWT) and BP neural network was presented. Through this method, the RGB color model character parameters of the maize seed crown part were obtained, then the three color values were processed and analyzed by the two-level DWT. The average of every band was selected as the input samples for BP neural network, and purity identification results of maize seed as the output samples of neural network. Results demonstrated that this method can identify the maize purity effectively with accurate identification rate reaching 94.5%.
引用
收藏
页码：253 / 258
页数：5
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