Analysis of Techniques to Tackle the Issues of Root Disease Detection- A Review

Authors

  • Hardeep Singh  Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar, Punjab, India
  • Sandeep Sharma  Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar, Punjab, India

Keywords:

Fruit Disease, Image classification, pre-processing, Segmentation, Clustering, Classification, MSVM

Abstract

Agriculture is the mother of all societies. It has assumed a vital part in the advancement of human development. Diseases in organic product cause significant issue in agrarian industry and furthermore cause monetary loss. The diseases in natural products diminish the yield and furthermore crumble the assortment and its pull back from the cultivation. So, prior detection of symptoms of organic product disease is required. This paper holds a study on natural product disease detection utilizing picture handling procedure. Advanced picture preparing is quick and exact method for detection of diseases in organic products. ID and arrangement of diseases of organic products are done through different calculations. This paper presents organic product disease distinguishing proof and grouping strategies .Although diseases and creepy crawly vermin can cause extensive yield misfortunes or convey demise to plants and it's likewise specifically influence to human wellbeing. These require cautious finding and opportune taking care of to shield the harvests from overwhelming misfortunes. In plant, diseases can be found in different parts, for example, natural product, stem and takes off. This paper speaks to the review of different methodologies for division strategy alongside highlight extraction and classifiers for detection of diseases in natural product.

References

  1. A. Awate and D. Deshmankar, "Fruit Disease Detection using Color , Texture Analysis and ANN," pp. 970–975, 2015.
  2. M. Chetan Dwarkani, R. Ganesh Ram, S. Jagannathan, and R. Priyatharshini, "Smart farming system using sensors for agricultural task automation," Proc. - 2015 IEEE Int. Conf. Technol. Innov. ICT Agric. Rural Dev. TIAR 2015, no. Tiar, pp. 49–53, 2015.
  3. S. R. Dubey, "Detection and Classification of Apple Fruit Diseases using Complete Local Binary Patterns," 2012.
  4. "SURVEY ON MAJOR DISEASES OF VEGETABLE AND FRUIT CROPS Total Number of leaves / Fru it counted Sum of all disease ratings × 100 Total number of leaves / fru its × maximum rating value," vol. 35, no. September, pp. 423–429, 2010.
  5. M. Dewdney, "Fungal Diseases of Citrus Fruit and Foliage Foliar Fungal Diseases to be Covered."
  6. B. Blight, "1. Brown Blight."
  7. S. Von Broembsen and P. W. Pratt, "Common Diseases of Stone Fruit Trees and Their Control."
  8. K. J. Patil, M. Z. Chopda, and R. T. Mahajan, "Lipase biodiversity," Indian J. Sci. Technol., vol. 4, no. 8, pp. 971–982, 2011.
  9. S. Daliman, S. A. Rahman, and I. Busu, "Segmentation of Oil Palm Area Based on GLCM- SVM and NDVI," pp. 645–650, 2014.
  10. M. A. Jabbar, B. L. Deekshatulu, and P. Chandra, "Classification of Heart Disease Using K- Nearest Neighbor and Genetic Algorithm," Procedia Technol., vol. 10, pp. 85–94, 2013.
  11. I. K. A. Enriko, M. Suryanegara, and D. Gunawan, "Heart Disease Prediction System using k-Nearest Neighbor Algorithm with Simplified Patient â€TM s Health Parameters," vol. 8, no. 12, 1843.
  12. B. Veytsman, L. Wang, T. Cui, S. Bruskin, and A. Baranova, "Distance-based classifiers as potential diagnostic and prediction tools for human diseases," BMC Genomics, vol. 15 Suppl 1, no. Suppl 12, p. S10, 2014.
  13. M. M. El-Hattab, "Applying post classification change detection technique to monitor an Egyptian coastal zone (Abu Qir Bay)," Egypt. J. Remote Sens. Sp. Sci., vol. 19, no. 1, pp. 23–36, 2016.
  14. C. Chen, M. Won, R. Stoleru, and G. G. X. Member, "Energy-Efficient Fault-Tolerant Data Storage & Processing in Mobile Cloud," vol. 3, no. 1, pp. 1–14, 2014.
  15. D. Bui, S. Hussain, E. Huh, and S. Lee, "Adaptive Replication Management in HDFS based on Supervised Learning," vol. 4347, no. c, pp. 1–14, 2016.
  16. "One-Pass Preprocessing Algorithm," pp. 851–853, 1988.
  17. M. K. R. Gavhale, "Unhealthy Region of Citrus Leaf Detection Using Image Processing Techniques," pp. 2–7, 2014.
  18. C. Engineering, A. Kumar, and G. S. Gill, "Automatic Fruit Grading and Classification System Using Computer Vision : A Review," no. I, pp. 598–603, 2015.
  19. R. A. Sadek, "SVD Based Image Processing Applications : State of The Art , Contributions and Research Challenges," vol. 3, no. 7, pp. 26–34, 2012.
  20. "Noise image."
  21. Y. Wang, J. Wang, X. Song, and L. Han, "An Efficient Adaptive Fuzzy Switching Weighted Mean Filter for Salt-and-Pepper Noise Removal," vol. 23, no. 11, pp. 1582–1586, 2016.
  22. Y. I. Abramovich, O. Besson, S. Member, B. A. Johnson, and S. Member, "Conditional expected likelihood technique for compound Gaussian and Gaussian distributed noise mixtures," no. c, pp. 1–12, 2016.
  23. T. K. Djidjou, D. A. Bevans, S. Li, and A. Rogachev, "Observation of Shot Noise in Phosphorescent Organic Light-Emitting Diodes," vol. 61, no. 9, pp. 3252–3257, 2014.
  24. B. Ghandeharian, "Modified Adaptive Center Weighted Median Filter for Suppressing Impulsive Noise in Images," Int. J. Res. Rev. Appl. Sci., vol. 177, no. 4, pp. 1073–1087, 2009.
  25. E. Nikahd, P. Behnam, S. Member, R. Sameni, and S. Member, "High-Speed Hardware Implementation of Fixed and Run-time Variable Window Length 1-D Median Filters," vol. XX, no. c, pp. 1–5, 2015.
  26. N. Chithirala, A. Radhakrishnan, and P. O. Amritanagar, "Weighted Mean Filter for Removal of High Density Salt and Pepper Noise," pp. 1–4, 2016.
  27. P. Mehta and B. Shah, "Review on Techniques and Steps of Computer Aided Skin Cancer Diagnosis," Procedia - Procedia Comput. Sci., vol. 85, no. Cms, pp. 309–316, 2016.
  28. N. Situ, X. Yuan, N. Mullani, and G. Zouridakis, "AUTOMATIC SEGMENTATION OF SKIN LESION IMAGES USING EVOLUTIONARY STRATEGY 2 . Engineering Technology Department , University of Houston," pp. 1–4.
  29. R. Parekh, "Analysis Diagnosis," pp. 28–37, 2012.
  30. J. K. Prasanna and A. N. Rajagopalan, "Image restoration using the particle filter : handling non-causality," vol. 153, no. 5, pp. 650–656, 2006.
  31. A. Wolke, M. Bichler, and T. Setzer, "Planning vs . dynamic control : Resource allocation in corporate clouds," vol. 7161, no. c, pp. 1–14, 2014.

Downloads

Published

2018-02-28

Issue

Section

Research Articles

How to Cite

[1]
Hardeep Singh, Sandeep Sharma, " Analysis of Techniques to Tackle the Issues of Root Disease Detection- A Review, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.781-792, March-April-2018.