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Classification of Plants Using Invariant Features and a Neural Network

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Information and Communication Technology for Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 107))

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Abstract

This chapter presents leaf shape moment invariant features and a neural network approach to plant classification. Leaf image samples for plant species were processed in order to find leaf shape patterns. Further leaf shape moment invariant features were extracted and then, by using a regularized neural network, plant classification accuracy was studied. Leaf image samples of five different plants were taken for classification. Invariant features are significant for classifying plants with leaves of similar shapes. A regularized neural network was used for plant classification, based on leaf shape moment invariant features. The result of the neural network model was observed for invariant features and their combination with shape features. Eighteen shape features and seven of Hu’s invariant features were extracted from sample images of leaves from five different plant classes.

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References

  1. Agarwal, S., Swetapadma, A., Panigrahi, C.: An improved method using artificial neural network for fault detection and fault pole identification in voltage source converter-based high-voltage direct current transmission lines (research article). Comput. Eng. Comput. Sci. Special Issue (first online: 9 August 2017); Arab J Sci Eng (2017). https://doi.org/10.1007/s13369-017-2791-9

    Article  Google Scholar 

  2. Ayoobkhan, M.U.A., Chikkannan, E., Ramakrishnan, K.: Feed-forward neural network-based predictive image coding for medical image compression (Research Article). Comput. Eng. Comput. Sci. Special Issue (first online: 25 October 2017); Arab J Sci Eng (2017). https://doi.org/10.1007/s13369-017-2837-z

    Article  Google Scholar 

  3. Wang, X.F., et al.: Recognition of leaf images based on shape features using a hypersphere classifier. In: Paper presented at International Conference on Intelligent Computing, 23–26 August 2005, vol. 3644, pp. 87–96. Hefei, China (2005)

    Google Scholar 

  4. Wu, S.G., et al.: A leaf recognition algorithm for plant classification using probabilistic neural network. In: Paper presented at 2007 IEEE International Symposium on Signal Processing and Information Technology, 15–18 December 2007, Giza, pp. 11–16 (2007)

    Google Scholar 

  5. Saad, P.: Feature extraction of trademark images using geometric invariant moment and zernike moment—a comparison. Chiang Mai J. Sci. 31, 217–222

    Google Scholar 

  6. Suk, T., Flusser, J., Novotný, P.: Comparison of leaf recognition by moments and Fourier descriptors. In: Wilson, R., et al. (eds.), CAIP 2013, Part I. LNCS 8047, pp. 221–228 (2013)

    Chapter  Google Scholar 

  7. Zulkifli, Z.: Plant leaf identification using moment invariants and General Regression neural network. In: Paper presented at 2011 11th International Conference on Hybrid Intelligent Systems (HIS), 12/2011

    Google Scholar 

  8. Chaki, J., Parekh, R.: Plant recognition using shape based features and neural network. Int. J. Adv. Comput. Sci. Appl. 2(10) (2011)

    Google Scholar 

  9. Kadir, A., Nugroho, L.E., Susanto, A., Santosa, P.I.: Leaf classification using shape, color, and texture features. Int. J. Comput. Trends Technol., 225–230 (2011)

    Google Scholar 

  10. Kadir, A., Nugroho, L.E., Susanto, A., Santosa, P.I.: A comparative experiment of several shape methods in recognizing plants. Int. J. Comput. Sci. Inf. Technol. 3(3), 256–263 (2011)

    Article  Google Scholar 

  11. Fang, H., Huijie, L.: Plant leaves recognition and classification model based on image features and neural network. Int. J. Comput. Sci. 11(2), No. 1, March (2014)

    Google Scholar 

  12. Bhardwaj, A., Kaur, M., Kumar, A.: Recognition of plants by leaf image using moment invariant and texture analysis. Int. J. Innov. Appl. Stud. 3(1), 237–248 (2013)

    Google Scholar 

  13. Salve, P., Sardesai, M., Manza, R., Yannawar, P.: Identification of the plants based on leaf shape descriptors. In: Proceedings of Second International Conference on Computer and Communication Technologies, Advances in Intelligent Systems and Computing, vol. 379, pp. 85–102 (2016)

    Google Scholar 

  14. ICL plant leaf image data set, Intelligenta set, Intelligent Computing Laboratory, Chinese Academy of Sciences. http://www.intelengine.cn/dataset/index.html, 2010–1012

  15. Amlekar, M.M., Gaikwad, A.T.: Leaf shape extraction for plant classification. In: Paper presented at IEEE International Conference on Pervasive Computing (ICPC), -1-4799-6272-3/15/2015

    Google Scholar 

  16. Huang, J., Leng, J.: Analysis of Hu’s moments invariants on image scaling, rotation. In: Proceedings of International Conference on Computer Engineering and Technology, pp. 476–480

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dr. Babasaheb Ambedkar, Marathwada University, Aurangabad, Maharashtra, India

    Manisha M. Amlekar, Mouad M. H. Ali & Ashok T. Gaikwad

  2. Information system & Technology Center, Hodeidah University, Hodeidah, Yemen

    Mouad M. H. Ali

  3. Institute of Management Studies and Information Technology, Aurangabad, Maharashtra, India

    Manisha M. Amlekar & Ashok T. Gaikwad

Authors
  1. Manisha M. Amlekar
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  2. Mouad M. H. Ali
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  3. Ashok T. Gaikwad
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Corresponding author

Correspondence to Manisha M. Amlekar .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India

    Suresh Chandra Satapathy

  2. Sabar Institute of Technology, Gujarat Technological University, Ahmedabad, Gujarat, India

    Amit Joshi

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Amlekar, M.M., Ali, M.M.H., Gaikwad, A.T. (2019). Classification of Plants Using Invariant Features and a Neural Network. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems . Smart Innovation, Systems and Technologies, vol 107. Springer, Singapore. https://doi.org/10.1007/978-981-13-1747-7_13

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