Feature extraction of jujube fruit wrinkle based on the watershed segmentation

Zhang Junxiong, Ma Qingqin, Li Wei, Xiao Tingting


The degree of surface wrinkles on a dried jujube fruit (Ziziphus jujuba Mill.) is an important quality grading criterion. The aim of this research was to propose an image processing method based on the watershed segmentation to extract the wrinkle features of jujube fruits. Original images of jujube fruit taken under cyan light were transformed into grayscale images. The noise in these images was then removed by morphological reconstruction. The H-minima extended transformation was used to label the foreground of jujube fruit images after reconstruction, and the labeled foreground regions were segmented by a distance transform-based watershed algorithm. Then, the grayscale images were filtered with a local range filter. The segmentation function was obtained using the minima imposition method. Finally, a watershed segmentation was used to extract the wrinkle features of jujube fruits. Experiments on 304 images of jujube fruit showed that the accuracy of wrinkle-based grading obtained by the algorithm was 92.11%, which proved that this method could be used to classify jujube wrinkles.
Keywords: feature extraction, watershed segmentation, image processing, jujube fruit, wrinkle, quality grading
DOI: 10.25165/j.ijabe.20171004.2638

Citation: Zhang J X, Ma Q Q, Li W, Xiao T T. Feature extraction of jujube fruit wrinkle based on the watershed segmentation. Int J Agric & Biol Eng, 2017; 10(4): 165–172.


feature extraction, watershed segmentation, image processing, jujube fruit, wrinkle, quality grading


Liang H. On the actuality, existing problems and solutions to the industry of the Chinese jujube. Master’s dissertation. Xi’an: Shaanxi Normal University, 2006; 47p. (in Chinese)

Abbas M F, Al-Niami J H, Al-Sareh E A. The effect of ethephon on the ripening of fruits of jujube. Journal of Horticultural Science, 1994; 69(3): 465–466.

Cyong J C, Hanabusa K. Cyclic adenosine monophosphate in fruits of Zizyphus jujuba. Phytochemistry, 1980; 19(12): 2747–2748.

Lee D J, Archibald J K, Chang Y C, Greco C R. Robust color space conversion and color distribution analysis techniques for date maturity evaluation. Journal of Food Engineering, 2008; 88(3): 364–372.

Dahjye L, Robert S, James A, Steve M C. Development of a machine vision system for automatic date grading using digital reflective near-infrared imaging. Journal of Food Engineering, 2008; 86(3): 388–398.

Ohali Y A. Computer vision based date fruit grading system: design and implementation. Journal of King Saud University-Computer and Information Sciences, 2011; 23(1): 29–36.

Xue J L, Zhang S J, Zhang J J. Simultaneous detection of external and internal quality parameters of Huping jujube fruits using hyperspectral imaging technology. Spectroscopy and Spectral Analysis, 2015; 35(8): 2297–2302.

Li J B, Deng X W, Kan Z, Tian X S, Xie F. The method of automatic dried red Jujube hierarchy based on machine vision. Agricultural Mechanization Research, 2014; 2: 55–59. (in Chinese)

Zhao J W, Liu S P, Zou X B, Shi J Y, Yin X P. Recognition of defect Chinese dates by machine vision and support vector machine. Transactions of the CSAM, 2008; 39(3): 113–116. (in Chinese)

Luo H P, Lu Q P. Application of near-infrared topology method in the quality analysis of jujube of southern Xinjiang. Spectroscopy and Spectral Analysis, 2012; 32(3): 655–659.

Wu L G, He J G, Liu G S, Wang S L, He X G. Detection of common defects on jujube using Vis-NIR and NIR hyperspectral imaging. Postharvest Biology and Technology, 2016; 112: 134–142.

Wang L L. Research of non-destructive grading technology and detection equipment for Hami big jujubes based on computer vision. Master’s dissertation. Shihezi: Shihezi University, 2013; pp.31–34. (in Chinese)

Xia Y. Research about inspection technology on external feature of Xinjiang dry jujube based on machine vision technology. Master’s dissertation. Zhenjiang: Jiangsu University, 2013; pp.46–52. (in Chinese)

Zhan Y. Research of Southern Sinkiang Jujube color classification method based on machine vision. Master’s dissertation. Alaer: Tarim University, 2015; pp.37–44. (in Chinese)

Yuan S G, Wang M, Pan J, Hu F, Li D Y. A seamline optimization approach based on watershed segmentation for aerial image mosaicking. Acta Geodaetica Et Cartographica Sinica, 2015; 44(10): 1108–1116. (in Chinese)

Jones G. Image segmentation using texture boundary detection. Pattern Recognition Letters, 1994; 15(6): 533–541.

Shi C K. Research on digital LED lighting controller in machine vision. Master’s dissertation. Guangzhou: South China University of Technology, 2010; pp.62–71. (in Chinese)

Gonzalez R C, Woods R E. Digital image processing Second Edition. New Jersey: Prentice Hall Press, 2002; pp.617–626.

Yu W B. Image processing based on MATLAB. Beijing: Tsinghua University Publishing House Press, 2008; pp. 182–183. (in Chinese)

Soille P. Morphological image analysis principles and applications. New York: Springer-Verlag Press, 2008; pp.150–152.

GB/T 5835-2009. Dried Chinese jujubes. (in Chinese)

Full Text: PDF

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.