Journal of Guangxi Normal University(Natural Science Edition) ›› 2014, Vol. 32 ›› Issue (2): 14-19.

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The Algorithm of Identifying the Front Side of Bamboo Based on BP Neural Network

WANG Dong-xu, SONG Shu-xiang, JIANG Pin-qun   

  1. College of Electronic and Engineering, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2013-10-23 Online:2014-06-25 Published:2018-09-25

Abstract: In order to improve the low rate of detecting the front side of a bamboo in chip in the bamboo automatic detection field, the paper present an algorithm of identifying the front side of the bamboo chip based on BP neural network. A model of BP neural network wa built with three layers of three input and one output. The operation flow is as follow: extract the front and reverse side’s textural features and characteristic value of gray value, then import these data into the trained model, and at last calculate the predicting results. The experiment results show that the algorithm can identify 96% of the reverse side and 95% of the front side under the principle of minimum risk. Therefore, the stability of the algorithm is stronger than any other method with signal feature.

Key words: the front and reverse side of bamboo, neural network, textural features, characteristic value of gray value

CLC Number: 

  • TP391.41
[1] 高程程,惠晓威.基于灰度共生矩阵的纹理特征提取[J].计算机系统应用,2010,19(6):195-198.
[2] 李晓阳,唐普英.基于灰度共生矩阵的图像纹理特征提取分析[J].自动化信息,2012(9):28-30.
[3] JIN Hong-lei, ZHANG Zhen-hua, LI Li-yuan, et al. Surface roughness detection based on texture analysis[J].Journal of Image and Graphics,2000,5(7):612-615.
[4] 许舒雯,吴淑莲,李晖.基于灰度共生矩阵的人体皮肤纹理分析[J].激光生物学报,2011,20(3):324-428.
[5] 周品.Matlab神经网络设计与应用[M].北京:清华大学出版社,2013.
[6] 张国翊,胡铮.改进BP神经网络模型及其稳定性分析[J].中南大学学报:自然科学版,2011,42(1):115-124.
[7] 李建伟,程晓卿,秦勇.基于BP神经网络的城市轨道交通车辆可靠性预测[J].中南大学学报:自然科学版,2013(S1):42-46.
[8] TALEB A., BENYETTOU A. Arabic vowels fuzzy neural network recognition[J].Journal of Applied Sciences, 2010, 10 (10):848-851.
[9] RUAN Xiao-gang, DAI Li-zhen. Vehicle study with neural networks[J].Physics Procedia, 2012, 25:814-821.
[10] 李苏梅,韩国强,周咏梅.一种基于BP神经网络的颜色空间量化方案[J].广西师范大学学报:自然科学版,2008,26(1):232-235.
[11] 周华杰,李宁.基于神经网络集成的乳腺肿瘤诊断系统[J].广西师范大学学报:自然科学版,2006,24(4):199-202.
[12] LIN Cheng-jian, WANG Jun-guo, LEE Chi-yung. Pattern recognition using neural-fuzzy networks based on improved particle[J]. Expert Systems with Applications, 2009, 36(3):5402-5410.
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