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Journal of Tea Science ›› 2017, Vol. 37 ›› Issue (2): 182-190.

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Grading of Machine Picked Tea Based on Image Processing Technology and Neural Network

WU Zhengmin, CAO Chengmao*, XIE Chengjian, WU Jiasheng, HU Wangyang, WANG Tianyu   

  1. College of Engineering, Anhui Agricultural University, Hefei 230036, China
  • Received:2016-12-30 Revised:2017-02-26 Online:2017-04-15 Published:2019-08-22

Abstract: To solve the picking problem of famous green tea, a new technology was proposed to classify machine picked tea in this paper. Fresh tea leaves plucked by machine are often mixed, with tea stalks and have a high broken rate and thereby only suitable for making general green tea. The convex hull area, convex hull perimeter, long axial length, short axial length and other morphological features of machine plucked tea leaves were analyzed by Labview vision, image processing technology and neural network to screen high quality tea. Industrial CCD camera with appropriate optical system was used to collect object classification features. User interface was developed by Labview, which can realize the data interaction, convenient operation, short development cycle and meet different users’ requirements. Finally, sample test showed that the correct rate of tea classification could reach about 90%, which provides a good theoretical basis for further research of tea grading equipment.

Key words: machine plucked tea, grading, neural network, image processing technology

CLC Number: