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Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine

by Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 13
Year of Publication: 2018
Authors: Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur
10.5120/ijca2018917746

Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur . Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine. International Journal of Computer Applications. 181, 13 ( Aug 2018), 31-36. DOI=10.5120/ijca2018917746

@article{ 10.5120/ijca2018917746,
author = { Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur },
title = { Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2018 },
volume = { 181 },
number = { 13 },
month = { Aug },
year = { 2018 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number13/29880-2018917746/ },
doi = { 10.5120/ijca2018917746 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:05:54.663746+05:30
%A Nabodip Sutrodhor
%A Molla Rashied Hussein
%A Md. Firoz Mridha
%A Prokash Karmokar
%A Tasrifa Nur
%T Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 13
%P 31-36
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a Neural Network Ensemble (NNE) for Mango Leaf Ailment Detection (MLAD) system. At first, the images of Mango leaves were cropped, then were resized and converted to their value of threshold. After that, the feature extraction methodology was applied. For pattern recognition, NNE and SVM were used. Subsequently, test images of affected leaves were uploaded to the system and then were matched to the trained ailments. The training data and test data were cross-validated to sustain equilibrium among over-fitting and under-fitting issues.

References
  1. Anand Swaroop, Sidney J. Stohs, Manashi Bagchi, Hiroyoshi Moriyama, and Debasis Bagchi. "Mango (Mangifera indica Linn) and Anti-Inflammatory Benefits: Versatile Roles in Mitochondrial Bio-Energetics and Exercise Physiology." Functional Foods in Health and Ailment 8, no. 5 (2018): 267-279.
  2. K. Srunitha and D. Bharathi. "Mango Leaf Unhealthy Region Detection and Classification." In Computational Vision and Bio Inspired Computing, pp. 422-436. Springer, Cham, 2018..
  3. A. Camargo and J. S. Smith. "An image-processing based algorithm to automatically identify plant ailment visual symptoms." Biosystems engineering 102, no. 1 (2009): 9-21.
  4. Bikash Chandra Karmokar, Mohammad Samawat Ullah, Md Kibria Siddiquee, and Kazi Md Rokibul Alam. "Tea leaf ailments recognition using neural network ensemble." International Journal of Computer Applications 114, no. 17 (2015).
  5. Panagiotis Tzionas, Stelios E. Papadakis, and Dimitris Manolakis. "Plant leaves classification based on morphological features and a fuzzy surface selection technique." In Fifth international conference on technology and automation, Thessaloniki, Greece, pp. 365-370. 2005.
  6. Michael Egmont-Petersen, Dick de Ridder, and Heinz Handels. "Image processing with neural networks—a review." Pattern recognition 35, no. 10 (2002): 2279-2301.
  7. Sladojevic, Srdjan, Marko Arsenovic, Andras Anderla, Dubravko Culibrk, and Darko Stefanovic. "Deep neural networks based recognition of plant ailments by leaf image classification." Computational intelligence and neuroscience 2016.
  8. Melissa B. Riley, Margaret R. Williamson, and Otis Maloy. "Plant ailment diagnosis." The plant health instructor (2002).
  9. Nur Badariah Ahmad Mustafa, Syed Khaleel Ahmed, Zaipatimah Ali, Wong Bing Yit, Aidil Azwin Zainul Abidin, and Zainul Abidin Md Sharrif. "Agricultural produce sorting and grading using support vector machines and fuzzy logic." In Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on, pp. 391-396. IEEE.
  10. Imran Maqbool, Salman Qadri, Dost Muhammad Khan, and Muhammad Fahad. "Identification of Mango Leaves by Using Artificial Intelligence." International Journal of Natural and Engineering Sciences 9, no. 3 (2015): 45-53.
  11. Maureen Caudill, "Neural networks primer, part VIII." AI Expert 4, no. 8 (1989): 61-67.
  12. Egmont-Petersen, Michael, W. R. M. Dassen, and Johan HC Reiber. "Sequential selection of discrete features for neural networks–A Bayesian approach to building a cascade." Pattern Recognition Letters 20, no. 11-13 (1999): 1439-1448.
  13. Gaurav Kumar and Pradeep Kumar Bhatia. "A detailed review of feature extraction in image processing systems." In Advanced Computing & Communication Technologies (ACCT), 2014 Fourth International Conference on, pp. 5-12. IEEE, 2014.
  14. Dong ping Tian, "A review on image feature extraction and representation techniques." International Journal of Multimedia and Ubiquitous Engineering 8, no. 4 (2013): 385-396.
  15. Dengsheng Zhang and Guojun Lu, "Review of shape representation and description techniques." Pattern recognition 37, no. 1 (2004): 1-19.
  16. Devashish Pujari, Rajesh Yakkundimath, and Abdulmunaf S. Byadgi. "SVM and ANN based classification of plant ailments using feature reduction technique." IJIMAI 3, no. 7 (2016): 6-14.
  17. Yuan Tian, Chunjiang Zhao, Shenglian Lu, and Xinyu Guo. "SVM-based multiple classifier system for recognition of wheat leaf ailments." In World Automation Congress (WAC), 2012, pp. 189-193. IEEE, 2012.
  18. Santanu Phadikar and Jaya Sil. "Rice ailment identification using pattern recognition techniques." In Computer and Information Technology, 2008. ICCIT 2008. 11th International Conference on, pp. 420-423. IEEE, 2008.
  19. Ajay A. Gurjar and Viraj A. Gulhane. "Ailment detection on cotton leaves by eigenfeature regularization and extraction technique." International Journal of Electronics, Communication and Soft Computing Science & Engineering (IJECSCSE) 1, no. 1 (2012): 1.
  20. Rakesh Kaundal, Amar S. Kapoor, and Gajendra PS Raghava. "Machine learning techniques in ailment forecasting: a case study on rice blast prediction." BMC bioinformatics 7, no. 1 (2006): 485.
  21. MS Prasad Babu and B. Srinivasa Rao. "Leaves recognition using back propagation neural network-advice for pest and ailment control on crops." IndiaKisan. Net: Expert Advisory System (2007).
  22. Isabelle Guyon and André Elisseeff. "An introduction to feature extraction." In Feature extraction, pp. 1-25. Springer, Berlin, Heidelberg, 2006.
  23. Melville and Mooney, “Creating Diverse Ensemble Classifiers to Reduce Supervision”, PhD Thesis, Department of Computer Sciences, University of Texas at Austin, November 2005.
  24. Hafiz T. Hassan, Muhammad U. Khalid, and Kashif Imran. "Intelligent Object and Pattern Recognition using Ensembles in Back propagation neural network." International Journal of Electrical & Computer Sciences (IJECS-IJENS) Vol 10 (2010).
  25. Robi Polikar, "Ensemble based systems in decision making." IEEE Circuits and systems magazine 6, no. 3 (2006): 21-45.
  26. Philipp, Isabelle, and Thomas Rath. "Improving plant discrimination in image processing by use of different colour space transformations." Computers and electronics in agriculture 35, no. 1 (2002): 1-15.
  27. Jagadeesh D. Pujari, Rajesh Yakkundimath, and Abdulmunaf S. Byadgi. "Recognition and classification of normal and affected agriculture produce using reduced color and texture features." International Journal of Computer Applications 93, no. 11 (2014).
  28. Jagadeesh D. Pujari, Rajesh Yakkundimath, and Abdulmunaf Syedhusain Byadgi. "Automatic fungal disease detection based on wavelet feature extraction and PCA analysis in commercial crops." International Journal of Image, Graphics and Signal Processing 6, no. 1 (2013): 24-31.
  29. P S. Landge, Patil S A., Khot D S., Otari O D. and Malavkar U G, Automatic Detection and Classification of Plant Ailment through Image Processing, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.3, Issue.7, July 2013, pp.798-801.
  30. S. Prasad, Piyush Kumar., Hazra R. and Ajay Kumar, Plant Leaf Ailment Detection Using Gabor Wavelet Transform, Proceedings of 3rd International Conference on Swarm, Evolutionary, and Memetic Computing, Springer-Verlag, Berlin, Heidelberg, 2012.
  31. J D Pujari, Content Based Image Retrieval Using Color and Texture Features, Ph.D. Thesis, Gulburga University, Gulburga, 2008.
  32. A N. Rathod, Tanawal B. and Shah V, Image Processing Techniques for Detection of Leaf Ailment, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.3, Issue.11, November 2013, pp.397-399.
  33. N. Razmjooya, Mousavib B S. and Soleymani F, A Real Time Mathematical Computer Method for Potato Inspection Using Machine Vision, Computers and Mathematics with Applications, Vol. 63, 2012, pp.268–279.
  34. Savakar D G. and Anami B S, Improved Method for Identification and Classification of Foreign Bodies Mixed Food Grains Image Samples, International Journal of Artificial Intelligence and Machine Learning, Vol.9, Issue.1, 2009, pp.1-8.
  35. Sungkur R K., Baichoo S. and Poligadu A, 2013, An Automated System to Recognize Fungi-caused Ailments on Sugarcane Leaves, Proceedings of Global Engineering, Science and Technology Conference, Singapore, 3-4 October, 2013.
  36. Vibhute A. and Bhode S K, Applications of Image Processing inAgriculture: A Survey, International Journal of Computer ApplicationsVol. 52, Issue. 2, August 2012, pp.34-40.
  37. Dheeb Al Bashish, Malik Braik, and Sulieman Bani-Ahmad, “A Framework for Detection and Classification of Plant Leaf and Stem Ailments,” Department of Information Technology, IEEE International Conference on Signal and Image zProcessing, 2010.
  38. S. Ananthi, S. Vishnu Varthini, “Detection and classification of plant leaf ailments,”International Journal of Research in Engineering & Applied Sciences, Volume 2, Issue 2 (February 2012), ISSN: 2249-3905, 2012.
  39. Jiazhi Pan, Yong He, “Recognition of plants by leaves digital image and neural network,” International Conference on Computer Science and Software Engineering,IEEE Computer Society, 2008.
  40. Xinhong Zhang, Fan Zhang, “Images Features Extraction of Tobacco Leaves,”Congress on Image and Signal Processing, IEEE Computer Society, 2008.
  41. A. Meunkaewjinda, P. Kumsawat, K. Attakitmongcol and A. Srikaew,“Grape leaf ailment detection from color imagery using hybrid intelligent system,” IEEE Proceedings of ECTI-CON, 2008.
  42. Zulkifli Bin Husin, Abdul Hallis Bin Abdul Aziz, Ali Yeon Bin Md Shakaff, Rohani Binti S Mohamed Farook, “Feasibility Study on Plant Chili Ailment Detection Using Image Processing Techniques,” Third International Conference on Intelligent Systems Modelling and Simulation, IEEE Computer Society, 2012
  43. Panagiotis Tzionas, Dimitris Manolakis, Stelios E. Papadakis “Plant leaves classification based on morphological features and a fuzzy surface selection technique.”
  44. Dr. V.S.Rajpurohit, Shruti Bhat, Shreya Devurkar, Shubhangi Patil, Supriya Sirbi, “Application of Image Processing Techniques in Object Shape Recognition”,International Journal of Latest Trends in Engineering and Technology (IJLTET), 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Neural Network Ensemble Pattern Recognition Support Vector Machine Mango Leaf Ailment Detection Image Processing Automated System

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