Development of an automatic sorting system for fresh ginsengs by image processing techniques

This study was conducted with the objective of implementing a smart IoT (internet of things) factory consisting of an automatic 6-year-old fresh ginseng grade classification device. Conventionally, washed 6-year-old ginseng from farmlands is manually sorted into three grades using classification criteria such as weight and shape. However, the cost associated with this classification process has been on the increase. Consequently, to reduce this associated cost, we developed an automatic ginseng sorting device that classifies 6-year-old ginseng according to weight and shape via image processing and sends the classification results to a factory server over a network. Evaluations conducted of the performance of the developed machine using 100 units of 6-year-old ginseng showed that it has a high recognition rate, with an accuracy of 94% for Grade 1, 98% for Grade 2, and 90% for Grade 3.

[1]  Marco Roccetti,et al.  A practical computer based vision system for posture and movement sensing in occupational medicine , 2017, Multimedia Tools and Applications.

[2]  Kuei-Fang Hsiao,et al.  Integrating body language movements in augmented reality learning environment , 2011, Human-centric Computing and Information Sciences.

[3]  이명구,et al.  Image Analyzer를 이용한 수삼등급의 자동판정 II.수삼의 적변판정 ( Automatic Decision-Making on the Grade of 6 Year-Old Fresh Ginseng (Panax ginseng C.A. Meyer) by an Image Analyzer II. Decision of Rusty Root of Ginseng ) , 2002 .

[4]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[5]  Hong Yan,et al.  Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition , 1996, Advances in Fuzzy Systems - Applications and Theory.

[6]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[7]  Sanghoon Kim,et al.  Parallel implementation of color-based particle filter for object tracking in embedded systems , 2016, Human-centric Computing and Information Sciences.

[8]  Marco Roccetti,et al.  Playing into the wild: A gesture-based interface for gaming in public spaces , 2012, J. Vis. Commun. Image Represent..

[9]  Chan-Moon Chung,et al.  Comparison of Grade of Raw and Red Ginseng on each Factor of Quality in Korean and American Ginseng , 2006 .

[10]  Mao-Jiun J. Wang,et al.  Image thresholding by minimizing the measures of fuzzines , 1995, Pattern Recognit..

[11]  Kadayanallur Mahadevan Prabusankarlal,et al.  Assessment of combined textural and morphological features for diagnosis of breast masses in ultrasound , 2015, Human-centric Computing and Information Sciences.

[12]  H. D. Cheng,et al.  Thresholding using two-dimensional histogram and fuzzy entropy principle , 2000, IEEE Trans. Image Process..

[13]  Ling-Ling Wang,et al.  A fast multilevel thresholding method based on lowpass and highpass filtering , 1997, Pattern Recognit. Lett..