Smart Farming Using Artificial Immune System Algorithm and Image Processing

Authors

  • Suman T. Mathematics Department, New Horizon College of Engineering, Bengaluru, India Author
  • Srinivasa G. Mathematics Department, New Horizon College of Engineering, Bengaluru, India Author

DOI:

https://doi.org/10.61841/dpz07588

Keywords:

Smart Farming, Artificial Immune System, Image Processing, Fruit Grading

Abstract

For any developing country like India, agriculture plays an important role and contributes a major part of the income to the country, so there is a need to grow and increase the yield effectively. In order to achieve the above objectives, one has to monitor the diseases starting from plantation to harvesting. In this paper we made an attempt to use Artificial Immune System(AIS) and image processing to (i) identify the diseases on fruits like grapes and apples and (ii) grade fruits. Disease identification aims at different features like color, texture, and shapes. Which are considered as feature vectors in this work. To extract color feature HSV histogram value concept is used; for texture wavelet transform method and for shape, morphology methods are used. After extracting the above-said features, we used the AIS algorithm as a classifier to classify the diseases, and it is observed that the color and morphology show better results than the texture. Grading of fruit aims at fruit segmentation, which calculates the healthy and infected portions of fruit. At the end we practically implemented the AIS algorithm, and results are obtained from MATLAB. 

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References

[1] Sindhuja Sankaran, Ashish Mishra et et.al, “A Review of Advanced Techniques for Detecting Plant Diseases in Computers and Electronics in Agriculture,” vol. 72, pp. 7-13, 2010.

[2] Murugesan, R., et al., “Optimization of Image Enhancement using an Artificial Immune System Algorithm,” IJMET, vol.8, pp. 184-192, 2017.

[3] Alexandre Meybeck and Vincent Gitz, “Leaf disease severity measurement uses image processing in agriculture,” Food Security Conference, 2012.

[4] K.P. Soman and K.L. Ramachandran, “Insight into Wavelet Transform Theory to Practice,” 2nd edition, PHI Publications, 2009.

[5] Sanjeev S. Sannakki, Vijay S. Rajpurohit, V. B. Nargund, Arun Kumar R., and Prema S. Yallur, “Leaf Disease Grading by Machine Vision and Fuzzy Logic,” International Journal of Computer and Technology Association, vol. 2 , pp. 1709-1716, Oct. 2011.

[6] N. Papamarkos, C. Strouthopool, I. Andreadis, “Multithresholding of color and gray-level images through a neural network technique,” Image and Vision Computing, Elsevier,l. 18, pp. 213-222, 2000.

[7] Boaz Lerner, Hugo Guterman, Mayer Aladjem, “Al network-based feature extraction: Comparative study of neural paradigms,” Pattern Recognition Letters, vol.20, pp. 7-14, 1999.

[8] Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing using MATLAB,” 3rd edition, Pearson Publications, 2009.

[9] Suma T and Murugesan R, “Subtask Scheduling of Industrial Robot in Cloud Manufacturing using Artificial Immune Algorithm,” Journal of Physics: Conference Series Vol 1000, pp 1-7, Feb 2018.

[10] B Monika Jhuria, Ashwani Kumar, Rushikes Borse, “Image Processing for Smart Farming: Detection of

Disease and Fruit Grading,” IEEE Second International Conference on Image Processing, vol 9, pp. 521 -

526, Dec. 2013.

[11] Xu Liming and Zhao Yancho, “Automatic Strawberry grading system based on image processing”

Computers and Electronics in Agriculture, vol1, pp. s32-s39, April 2010.

[12] Haiwei Dong, Nikolaos Mavridis and Abdulhamid Haidar, "Image-Based Date Fruit Classificatio”n,

International Congress on Ultra Modern Telecommunications and Control Systems, vol. IV, 2012.

[13] Saravanan, S., SS Aravinth, and M. Rameshkumar. "A Novel Approach in Agriculture Automation for Sugarcane Farming by Human-Assisting Care Robot." International Journal of Agricultural Science and Research (IJASR) 7.4 (2017): 107-112

[14] Shireesha, K., et al. "Correlates of Profile and Attitude of Youth towards Farming." International Journal of Agricultural Science and Research (IJASR) 7.1 (2016): 43-52

[15] Barusu, Madhusudhana Reddy, et al. "Irrigation, Fertilizing, and Weed Cutting in the Row Crops with IOT-Controlled Robot." International Journal of Mechanical and Production Engineering Research and Development (IJMPERD) 8, Special Issue 3 (2018):512-518.

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Published

31.07.2020

How to Cite

T. , S., & G. , S. (2020). Smart Farming Using Artificial Immune System Algorithm and Image Processing. International Journal of Psychosocial Rehabilitation, 24(5), 6812-6816. https://doi.org/10.61841/dpz07588