CFP last date
20 May 2024
Reseach Article

Detection of Disease in Plant Leaf using Image Segmentation

by Nandini Kakran, Pratik Singh, K. P. Jayant
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 35
Year of Publication: 2019
Authors: Nandini Kakran, Pratik Singh, K. P. Jayant
10.5120/ijca2019919229

Nandini Kakran, Pratik Singh, K. P. Jayant . Detection of Disease in Plant Leaf using Image Segmentation. International Journal of Computer Applications. 178, 35 ( Jul 2019), 29-32. DOI=10.5120/ijca2019919229

@article{ 10.5120/ijca2019919229,
author = { Nandini Kakran, Pratik Singh, K. P. Jayant },
title = { Detection of Disease in Plant Leaf using Image Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2019 },
volume = { 178 },
number = { 35 },
month = { Jul },
year = { 2019 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number35/30769-2019919229/ },
doi = { 10.5120/ijca2019919229 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:52:19.896655+05:30
%A Nandini Kakran
%A Pratik Singh
%A K. P. Jayant
%T Detection of Disease in Plant Leaf using Image Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 35
%P 29-32
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Disease have a worse effect on crop plants and directly or indirectly impact the agriculture production and market access. Farmers experience difficulties as crop effected and also having difficulties in change from one disease control policy to another. Plant disease diagnosis is a science as well as technology. Disease reduces both the quality and quantity of agriculture production as well as causes the economic losses. Now a days, plant disease detection has received increasing attention. In most of the cases, diseases are seen on leaf or stem part of the plant. In this paper, we will define the types of disease with their symptoms and how the image segmentation technique is used in detection of leaf disease.

References
  1. Anand H. Kulkarni, Ashwin Patil R. K., Applying image processing technique to detect plant diseases, International Journal of Modern Engineering Research, vol.2, Issue.5, pp: 3661-3664, 2012.
  2. Tushar H. Jaware, Ravindra D. Badgujar and Prashant G. Patil, Crop disease detection using image segmentation, National Conference on Advances in Communication and Computing, World Journal of Science and Technology, pp:190-194, Dhule, Maharashtra, India, 2012.
  3. Babu, MSP and B.Srinivas Rao, 2010, “Leaves recognition using back- propagation neural network advice for pest and disease control on crops technical report” , Department of Computer Science and Systems Engineering Andra University, India.
  4. Basvaraj. S. Anami, J.D. Pujari, Rajesh, Yakkuundimath, “Identification and classification of normal and affected Agriculture/ horiculture produce based on combined color and texture feature extraction”, International Journal of Computer Application in Engineering Science [vol 1 issue 3, September 2011] ISSN; 2231-4946
  5. Hada Onsi, Ahmed Rafea, Salwa- El- Gammal, “Detecting Leaf Spots in Cucumber crop using fuzzy clutering Algorithm”, Central Lab. For Agricultural Expert System (CLAES)
  6. Dheeb Al Bashish, Malik Braik, and Sulieman Bani-Ahmad,” A Framework for Detection and Classification of Plant Leaf and Stem Diseases”, 2010 International Conference on Signal and Image Processing, pp 113-118.
  7. T. Rumph, A.- K.Mahlein, U. steiner, E.-C.Oerke, H.- W. Dehne, L.Plumer, “Early detection and classification of plant disease with support vector m achines based on hyperspectral reflectance”, Computer and Electronics in Agriculture ELSEVIER
  8. S. Arivazhagan, R. Newlin Shebiah*, S. Ananthi and S. Vishnu Varthini, “Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features”, Agric Eng Int: CIGR Journal Open access at http://www.cigrjournal.org, March, 2013 Vol. 15, No.1 pp 211-217
  9. Amiya Halder and Nilavra Pathak, „‟An Evolutionary Dynamic Clustering Based Colour Image Segmentation”, International Journal of Image Processing (IJIP), Volume (4): Issue (6) pp 549-556
  10. Tianzi Jiang, Faguo Yang, Yong Fan and David J. Evans,” A Parallel Genetic Algorithm for Cell Image Segmentation”, Electronic Notes in Theoretical ComputerScience,URL:http://www.elsevier.nl/locate/entcs/volume46 (2001).html pages pp1-12Ms. Kiran R. Gavhale, Prof. Ujwalla Gawande
  11. “An Overview of the Research on Plant Leaves Disease detection using Image Processing Techniques”, IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 1, Ver. V (Jan. 2014), PP 10-16
  12. S. Phadikar, J. Sil, and A. K. Das,” Classification of Rice Leaf Diseases Based on Morphological Changes”, International Journal of Information and Electronics Engineering, Vol. 2, No. 3, May 2012
  13. S. Arivazhagan, R. Newlin Shebiah*, S. Ananthi and S. Vishnu Varthini, “ Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features”, Agric Eng Int: CIGR Journal Open access at http://www.cigrjournal.org, March, 2013 Vol. 15, No.1 pp 211-217
  14. Salem Saleh Al-amri, N.V. Kalyankar and Khamitkar S.D,” Image Segmentation by Using threshold Techniques”, Journal of Computing, Volume 2, Issue 5, May 2010, ISSN 151-9617 pp 83-86
  15. Sannakki S.S., Rajpurohit V.S., Nargund V.B., Arun Kumar R.and Yallur P.S.,” A Hybrid Intelligent System for Automated Pomgranate Disease detection and Grading”, International Journal of Machine Intelligence ISSN: 0975–2927 & E-ISSN: 0975–9166, Volume 3, Issue 2, 2011, pp-36-44.
  16. W. Frei and C. Chen, "Fast Boundary Detection: A Generalization and New Algorithm," IEEE Trans. Computers, vol. C-26, no. 10, pp. 988-998, Oct. 1977.
  17. R. C. Gonzalez and R. E. Woods, “Digital Image Processing”. Upper Saddle River, NJ: Prentice-Hall, 2001, pp. 572-585.
  18. Mr. Salem Saleh Al-amri, Dr. N.V. Kalyankar and Dr. Khamitkar S.D, “Image Segmentation by Using Edge Detection”, (IJCSE) International Journal on Computer Science and Engineering, Vol. 02, No. 03, 2010, pp 804-807.
  19. N. Senthilkumaran and R. Rajesh, “A Study on Split and Merge for Region based Image Segmentation”, Proceedings of UGC Sponsored National Conference Network Security (NCNS-08), 2008, pp.57-61.
  20. N. Senthilkumaran and R. Rajesh,” Edge Detection Techniques for Image Segmentation - A Survey”, Proceedings of the International Conference on Managing Next Generation Software Applications (MNGSA-08), 2008, pp.749-760. © 2009
  21. Mehmet Sezgin and Bu¨ lent Sankur, “Survey over image thresholding techniques and quantitative performance evaluation”, Journal of Electronic Imaging 13(1), (January 2004), pp 146–165.
  22. D. Grigaitis, R. Kirvaitis and R. Dobrovolskis,” Determination of twist gray matter and some dark features of human brain in the images of computer tomography,” Electronics and Electrical Engineering, Kaunas: Technologija, 2004, No.6(55), (55), 29 – 33s
Index Terms

Computer Science
Information Sciences

Keywords

Leaf disease symptoms of disease image segmentation