Herbal Plant Classification and Leaf Disease Identification Using MPEG-7 Feature Descriptor and Logistic Regression

  • Ajay RanaEmail author
  • Ankush Mittal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1048)


Plant disease classification, especially herbal plant disease classification is a prominent problem in the field of botany. It is compelling problem due to the heterogeneity among the plants of the same category and dearth of awareness about the immense medicinal properties of herbal leaf. By not only classifying herbal plant but also identifying the diseased and non-diseased traits among herbal plants will facilitate the naive population as well as herbal product manufacturing industry and pharmaceutical industry to enrich the global economy. In this paper, we have presented how MPEG-7 color and texture feature descriptors are incorporated with the traditional classifiers (for example, Logistic regression and Support Vector Machine, etc.) to yield very impressive results on wide range of classes. A total of two datasets: herbal plant dataset and leaf disease dataset are used to evaluate the results. This classification strategy is not only accurate but also very efficient in terms of number of computations needed and overall performance of the system. Comparison with other traditional features indicates the potential of MPEG-7 feature descriptors.


MPEG-7 Black rot Logistic regression Bacterial spot Cross entropy Haar transform 


  1. 1.
    Martınez, J.M.: MPEG-7 overview (version 10), vol. 3752. Technical report (2004)Google Scholar
  2. 2.
    Wu, S.G., Bao, F.S., Xu, E.Y., Wang, Y.-X., Chang, Y.-F., Xiang, Q.-L.: A leaf recognition algorithm for plant classification using probabilistic neural network. In: 2007 IEEE International Symposium on Signal Processing and Information Technology, pp. 11–16. IEEE (2007)Google Scholar
  3. 3.
    Hossain, J., Amin, M.A.: Leaf shape identification based plant biometrics. In: 2010 13th International Conference on Computer and Information Technology (ICCIT), pp. 458–463. IEEE (2010)Google Scholar
  4. 4.
    Du, J.-X., Wang, X.-F., Zhang, G.-J.: Leaf shape based plant species recognition. Appl. Math. Comput. 185(2), 883–893 (2007)zbMATHGoogle Scholar
  5. 5.
    Munisami, T., Ramsurn, M., Kishnah, S., Pudaruth, S.: Plant leaf recognition using shape features and colour histogram with K-nearest neighbour classifiers. Procedia Comput. Sci. 58, 740–747 (2015)CrossRefGoogle Scholar
  6. 6.
    Hernández-Serna, A., Jiménez-Segura, L.F.: Automatic identification of species with neural networks. PeerJ 2, e563 (2014)CrossRefGoogle Scholar
  7. 7.
    Begue, A., Kowlessur, V., Singh, U., Mahomoodally, F., Pudaruth, S.: Automatic recognition of medicinal plants using machine learning techniques. Int. J. Adv. Comput. Sci. Appl. 8(4), 166–175 (2017)Google Scholar
  8. 8.
    Mohanty, S.P., Hughes, D.P., Salathé, M.: Using deep learning for image-based plant disease detection. Front. Plant Sci. 7, 1419 (2016)CrossRefGoogle Scholar
  9. 9.
    Dhaygude, S.B., Kumbhar, N.P.: Agricultural plant leaf disease detection using image processing. Int. J. Adv. Res. Electr. Electron. Instrum. Eng. 2(1), 599–602 (2013)Google Scholar
  10. 10.
    Badnakhe, M.R., Deshmukh, P.R.: An application of K-means clustering and artificial intelligence in pattern recognition for crop diseases. In: International Conference on Advancements in Information Technology (2011)Google Scholar
  11. 11.
    Arivazhagan, S., Newlin Shebiah, R., Ananthi, S., Vishnu Varthini, S.: Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. Agric. Eng. Int. CIGR J. 15(1), 211–217 (2013)Google Scholar
  12. 12.
    Naikwadi, S., Amoda, N.: Advances in image processing for detection of plant diseases. Int. J. Appl. Innov. Eng. Manag. (IJAIEM) 2(11) (2013)Google Scholar
  13. 13.
    Patil, S.B., Bodhe, S.K.: Leaf disease severity measurement using image processing. Int. J. Eng. Technol. 3(5), 297–301 (2011)Google Scholar
  14. 14.
    Singh, V., Misra, A.K.: Detection of plant leaf diseases using image segmentation and soft computing techniques. Inf. Process. Agric. 4(1), 41–49 (2017)Google Scholar
  15. 15.
    Mittal, A., Cheong, L.-H.: Addressing the problems of Bayesian network classification of video using high-dimensional features. IEEE Trans. Knowl. Data Eng. 16(2), 230–244 (2004)CrossRefGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceGraphic Era Deemed To Be UniversityDehradunIndia

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