Advertisement

Mango Leaf Unhealthy Region Detection and Classification

  • K. SrunithaEmail author
  • D. Bharathi
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)

Abstract

Diseases in any plant decrease the productivity and quality of product. Identification of plant leaf diseases by naked human eye is very difficult. Image processing techniques can identify the diseased leaf by preprocessing and classifying leaf unhealthy regions. This paper delivers an implementation on Mango leaf unhealthy region detection and classification. In the Proposed work Multiclass SVM is used for diseases classification and segmentation through k-means. The experimental results show the effectiveness of the proposed method in recognizing the diseases affected mango leaf.

Keywords

Multi class SVM Image processing k-means clustering 

References

  1. 1.
    Anand, R., Veni, S., Aravinth, J.: An application of image processing techniques for detection of diseases on brinjal leaves using K-means clustering method. In: IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT (2016)Google Scholar
  2. 2.
    Pooja, A., Mamtha, R., Sowmya, V., Soman, K.P.: X-ray image classification based on tumor using GURLS and LIBSVM. In: International Conference on Communications and Signal Processing (ICCSP’16) (2016)Google Scholar
  3. 3.
    Krishnan, M., Sumithra, M.G.: A novel algorithm for detecting bacterial leaf scorch (BLS) of shade trees using image processing. In: IEEE 11th Malaysia International Conference on Communications (2013)Google Scholar
  4. 4.
    Arivazhagan, S., NewlinShebiah, R., Ananthi, S., Vishnu Varthini, S.: Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. AgricEngInt CIGR J. 15, 211–217 (2013)Google Scholar
  5. 5.
    Naikwadi, S., Amoda, N.: Advances in image processing for detection of plant diseases. Int. J. Appl. Innov. Eng. Manag. 2(11) (2013)Google Scholar
  6. 6.
    Arivazhagan, S., NewlinShebiah, R., Ananthi, S., Vishnu Varthini, S.: Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture feature. CIGR 15(1), 211–217 (2013)Google Scholar
  7. 7.
    Amoda, N., Naikwadi, S.: Advances in image processing for detection of plant diseases. Int. J. Appl. Innov. Eng. Manag. (IJAIEM) 2(11). ISSN: 2319-4847 (2013) Google Scholar
  8. 8.
    Jagtap, S.B., Hambarde, S.M.: Agricultural plant leaf disease detection and diagnosis using image processing based on morphological feature extraction. IOSR J. VLSI Signal Process. (IOSR-JVSP) 4(5), 24–30, Ver. I. e-ISSN: 2319-4200, p-ISSN: 2319-4197 (2014)Google Scholar
  9. 9.
    Gavhale, K.R., Gawande, U.: An overview of the research on plant leaves disease detection using image processing techniques. IOSR J. Comput. Eng. (IOSR-JCE) 16(1), 10–16, Ver. V. ISSN: 2278–8727 (2014)Google Scholar
  10. 10.
    Ratnasari, E.K., Mentari, M., Dewi, R.K., Hari Ginardi, R.V.: Sugarcane leaf disease detection and severity estimation based on segmented spots image. In: IEEE. ICTS 978-1-4799-6858-9/14/$31.00 © 2014Google Scholar
  11. 11.
    Fadzil, W.M.N.W.M., Rizam M.S.B.S., Jailani, R., Nooritawati, M.T.: Orchid leaf disease detection using border segmentation techniques. In: 2014 IEEE Conference on Systems, Process and Control (ICSPC 2014), Kuala Lumpur, Malaysia, 12–14 December 2014Google Scholar
  12. 12.
    Warne, P.P., Ganorkar, S. R.: Detection of diseases on cotton leaves using K-mean clustering method (IRJET) 02(04). e-ISSN: 2395 -0056 (2015)Google Scholar
  13. 13.
    Kaur, R., Kang, S.S.: An enhancement in classifier support vector machine to improve plant disease detection. In: IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education (MITE), pp. 135–140 (2015)Google Scholar
  14. 14.
    Khirade, S.D., Patil, A.B.: Plant disease detection using image processing. Int. Conf. Comput. Commun. Control Autom. 978-1-4799-6892-3/15 $31.00 © 2015 IEEEGoogle Scholar
  15. 15.
    Padmavathi, S., Saipreethy, M.S., Valliammai, V.: Indian sign language character recognition using neural networks. In: IJCA Special Issue on Recent Trends in Pattern Recognition and Image Analysis, vol. RTPRIA, pp. 40–45 (2013)Google Scholar
  16. 16.
    Dinesh Kumar, C.K., Manjusha, R., Latha, P.: Comparision of image classification methods on event data. Int. J. Applied Eng. Res. 10, 29631–29640 (2015)Google Scholar

Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Amrita School of Engineering, CoimbatoreAmrita Vishwa Vidyapeetham, Amrita UniversityCoimbatoreIndia

Personalised recommendations