Survey of rice seed quality analysis for varietal purity estimation by using image processing techniques

  • Authors

    • S. Durai
    • C. Mahesh
    • T. Sujithra
    • A. Suresh
    2018-02-05
    https://doi.org/10.14419/ijet.v7i1.7.9383
  • Computer vision, rice seed analysis, Quality factors of rice seed, rice seed varietal purity.

  •  In south India rice is the major food source and in agriculture, rice production covers more than 70 percentages of entire forming. But in recent the production only from south India not enough to satisfy the need of all, such a huge demand is there. The better production comes from the selection of good seeds. Up to now formers depend on two factors for selecting better seeds, One is the brand which is approved by some quality standards and second one is analyzed manually by experienced people. Both are risky one, we are not pretty much sure the accuracy of analyze. The second one is seeing and feeling. The inspection is not consistent also very time consuming. In the other way we can use computer vision technology to analyze the quality of the seeds. In recent years many of the big industries they are using computer vision technology with Digital Image Processing for many of the applications. In this Paper we are going to discuss the different seed quality analyzing methods and accuracy of result also. Moreover there are different factors and features are there for it, here we are going to study about varietal purity estimation by different methods.

  • References

    1. [1] Z.-y. Liu, F. Cheng, Y.-b. Ymg, and X.-q. Rao, "Identification of rice seed varieties using neural network," Journal of Zhejiang University Science. B, vol. 6, no. 11, pp. 1095-1100, 11 2005.

      [2] A G. OuYang and R. j. Gao et al, "An automatic method for identifying different variety of rice seeds using machine vision technology;' in 2010 Sixth Int. Con! on Natural Computation, vol. 1, Aug 2010, pp. 84--88.

      [3] P. T. T. Hong and T. T. T. H. et al., "Comparative study on vision based rice seed varieties identification," in Knowledge and Systems Engineering (KSE), 2015 Seventh Int. Con! on, Oct 2015, pp. 377-382

      [4] D.-W. Sun, Computer Vision Technology for Food Quality Evaluation. Elsevier, 2008.

      [5] Phan Thi Thu Hong, Tran Thi Thanh Hai, Le Thi Lan, Vo Ta Hoang and Nguyen Thi Thuy "Identification Of Seeds Of Different Rice Varieties Using Image Processing And Computer Vision Techniques" J. Sci. & Devel. 2015, Vol. 13, No. 6: 1036-1042

      [6] Archana Chaugule and Suresh N. Mali "Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties" Hindawi Publishing Corporation Journal of Engineering Volume 2014, Article ID 617263, 8 pages https://doi.org/10.1155/2014/617263.

      [7] S. Khunkhett, T. Remsungnen “Non-Destructive Identification Of Pure Breeding Rice Seed Using Digital Image Analysis†JICTEE-2014

      [8] S.J. Mousavirad, F. A. Tab, and K. Mollazade, "Design of an Expert System for Rice Kernel Identification using Optimal Morphological Features and Back Propagation Neural Network," International Journal of Applied information systems, vol. 3, pp. 33-37, 2012.

      [9] S.Durai, M.Thanjai Vadivel, T.Sujithra “Grading of Rice Quality by Chalky area analysis Using Simple Digital Image Processing Techniques†International Journal of Pure and Applied Mathematics Volume 114 No. 12 2017, 657-665.

      [10] http://www.knowledgebank.irri.org/

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  • How to Cite

    Durai, S., Mahesh, C., Sujithra, T., & Suresh, A. (2018). Survey of rice seed quality analysis for varietal purity estimation by using image processing techniques. International Journal of Engineering & Technology, 7(1.7), 34-37. https://doi.org/10.14419/ijet.v7i1.7.9383