The week's pick
Reseach Article
Analysis of Plant Diseases with Detection using Image Processing Methods
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 166 - Number 7 |
| Year of Publication: 2017 |
| Authors: Yatendra Kashyap, Tanuja Sharma, Syed Shahnawaz Ali |
10.5120/ijca2017914073
|
Yatendra Kashyap, Tanuja Sharma, Syed Shahnawaz Ali . Analysis of Plant Diseases with Detection using Image Processing Methods. International Journal of Computer Applications. 166, 7 ( May 2017), 28-31. DOI=10.5120/ijca2017914073
Abstract
Crop production is one of the major sources of earning and more than half of our population depends on agriculture for livelihood. Due to the factors like diseases, pest attack and sudden change in the weather condition, the productivity of the crop decreases. Traditional method of checking diseases in plants is through visualization but this method is not so relevant in detecting the diseases associated with plants. So we can provide a better alternative, fast and accurate detection by using image processing techniques which can be more reliable than some other old methods. Through this paper we proposed a methodology for the analysis and detection of plant diseases using digital image processing techniques. Because the fungus and bacteria kills the soya plant foliar and it spread in air and can also infect other plants also. So a close monitoring is required but as a human it is not possible to monitor the large area of land where the crop grows that problem is resolved by our proposed system.
References
- Dubey S., Dixit P., Singh h N., Gupta N, “ infected Part Detection using K-Means Clustering Segmentation Technique” International Journal of Artificial Intelligence and Interactive Multimedia, Vol. 2, No. 2.
- Blasco J., Alexios N., Molto E., “Machine Vision System for automatic quality grading of fruitproceeding of science direct, Automation and Emerging Technologies, pp. 415–423, 2003.
- Pujara j ., Vakundimath R., Byadgi A “image processing based detection of fungai disease of plants” Proceedings of ELSEVIER, international conference on information and communication technologies(ICICT2014). pp. 1802 -1808, 2014.
- Monika Jhuria, Ashwani Kumar and Rushik esh Borse, “Image processing for smart farming detection of disease and fruit grading,” IEEE 2nd International Conference on Image Information Processing (ICIIP), Shimla, pp 521-526, 2013.
- P.Revathi and M.Hemalatha, “Classification of Cotton Leaf Spot Diseases Using Image Processing Edge Detection Techniques,” IEEE International Conference on Emerging Trends in Science, Engineering and Technology (INCOSET), Tiruchirappalli, pp 169-173, 2012.
- Dubey SR, Jalal AS. Adapted Approach for Fruit Disease Identification using Images. International Journal of Computer Vision and Image Processing. 2012;2(3):51–65.
- Patil Sanjay B et al. Leaf disease severity measurement using image processing. Int J Eng Technol 2011; 3(5):297–301.
- Vijayaraghavan V, Garg A, Wong CH, Tai K. Estimation of mechanical properties of nanomaterials using artificial intelligence methods. Appl Phys A 2013:1–9.
- Ravi C.Shinde, Jibu Mathew C and Prof. C. Y. Patil”Segmentation Technique for Soybean Leaves Disease Detection” International Journal of Advanced Research (2015), Volume 3, Issue 5, 522-528
- Xiao-dan M, Hai-ou G, Fen T. Investigation on the Extraction of Soybean Brown Spot Based on Improved Genetic Algorithm. Information Science and Management Engineering. 2010;1:14 - 17. Xi'an: IEEE.
- Weizheng S, Yachun W, Zhanliang C, Wei H. Grading mathod of leaf spotInfection based image processing” International conference on comuter science and software engineering. 2008;491-494. Wuhan, Hube: IEEE. doi:10.1109/CSSE.2008.1649
- Ms. Chinki Chandhok, Mrs. Soni Chaturvedi, Dr. A. A. Khurshid “An Approach to Image Segmentation Using K-means Clustering Algorithm” International Journal of Information Technology (IJIT) ,Volume-1,Issue-1,August 2012, ISSN 2279-008X.
- Cui D, Zhang Q, Li M, Zhao Y, Hartman GL. Detection of soybean rust using a multispectral image sensor”, Sens. & Instrumen. Food Qual. 2009;3:49-56.
- Rabia Masood, S.A. Khan, M.N.A. Khan , Plants Disease Segmentation using Image Processing I.J. Modern Education and Computer Science, 2016, 1, 24-32
- Yinmao Song, Zhihua Diao, Yunpeng Wang, Huan Wang Image Feature Extraction of Crop Disease 2012 IEEE Symposium on Electrical & Electronics Engineering (EEESYM). College of Electrical and Information Engineering Zhengzhou University of Light Industry.
- S. Arivazhagan, R. Newlin Shebiah*, S. Ananthi, S. Vishnu Varthini. Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. March, 2013 Agric Eng Int: CIGR Journal. Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi Tamilnadu, 626 005, India.
- N.Valliammai', S.N.Geethaiakshmi2. Multiple noise reduction using hybrid method for leaf recognition. H. Al-Hiary, S. Bani-Ahmad, M. Reyalat, M. Braik and Z. Al Rahamneh. Jordan. Fast and Accurate Detection andClassification of Plant Diseases. International Journal of Computer Applications (0975 – 8887) Volume 17– No.1, March 201. Department of Information Technology, Al-Balqa’ Applied University, Salt Campus.
- Anup Vibhute Assistant Professor, BMIT, Solapur(India) and S K Bodhe Phd, Professor, Applications of Image Processing in Agriculture: A Survey. International Journal of Computer Applications (0975 – 8887) Volume 52– No.2, August 2012. College of Engineering, Pandharpur.
- Crop pest surveillance and advisory project (CROPSAP) in maharashtra (2011-12)
- Keyvan Asefpour Vakilian, Jafar Massah. Development and performance evaluation of a robot to early detection of nitrogen deficiency in greenhouse cucumber (cucumis sativus) with machine vision. International Journal of Agriculture: Research and Review. Department of Agrotechnology, College of Abouraihan, University of Tehran, Tehran, Iran.
- Mr. Jagan Bihari Padhy, Devarsiti Dillip Kumar, Ladi Manish and Lavanya Choudhry” Leaf Disease Detection Using K-Means Clustering And Fuzzy Logic Classifier”IJSET, Volume 02, No. 5, May 2016,2395-0900.
- Abdallah A. Alshennawy, and Ayman A. Aly,” Edge Detection in Digital Images Using Fuzzy Logic Technique”, World Academy of Science, Engineering and Technology 27 2009.
- Sunita I. Naik, Vivekanandreddy, S. S. Sannakki” Plant Disease Diagnosis System for Improved Crop Yield”, International Journal of Innovations in Engineering and Technology (IJIET), Vol. 4 Issue 1 June 2014, ISSN: 2319 – 1058.
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