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IJSTR >> Volume 4 - Issue 3, March 2015 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Orchid Classification, Disease Identification And Healthiness Prediction System

[Full Text]

 

AUTHOR(S)

K. W. V Sanjaya, H. M. S. S Vijesekara, I. M. A. C. Wickramasinghe, C. R. J. Amalraj

 

KEYWORDS

 

ABSTRACT

Abstract: Floriculture has become one of Sri Lanka’s major foreign exchange ventures and it has grown substantially during the last few years. Currently, we can find three major types of growers in floriculture. They are Large Commercial Ventures, Middle Level growers and Village Level growers. Both Middle Level and Village level growers usually go for low cost cultivation with minimum advanced techniques, sticking to conventional methods. Orchid cultivation is more pleasurable and profitable than any other floriculture ventures. As the orchid cultivation is so pleasurable we can introduce another group of growers who cultivate orchid in their home gardens for making their home gardens beautiful. But the problem is that most of these growers may not have the knowledge to identify the specie of the plants as there are a number of similar looking plants which are in different species. And also they may not have the knowledge about the orchid diseases. Because of that they may not be able to get the maximum outcome from their cultivations. So the aim of our project is to address the above mentioned issues by introducing a system which can identify orchid species & diseases and predict the healthiness of the orchid plants. The only input to this system is an image of an orchid leaf and the system will provide the orchid specie name, diseases if there any, healthiness of the orchid plant and suggestions to overcome the issues associated with the orchid plant as the output. We identify the orchid species and diseases by extracting the features of orchid plant leaf in the input image using image processing technics and with the use of data mining technics we predict the healthiness of the orchid plant. So, this system will be a great help for the people who love to grow orchids but don’t have knowledge about the orchid species and diseases. And also they will be able to find the healthiness of their orchid plants.

 

REFERENCES

[1] Jayamala K. Patil, Raj Kuma ADVANCES IN IMAGE PROCESSING FOR DETECTION OF PLANTDISEASES Bharti Vidyapeeth C.O.E. Kolhapur, Bhatati Vidyapeeth (Deemed Univ.) Pune Defence Institute of Advanced Tech.,Deemed University, Girinagar,Pune.

[2] Abdul Kadir, Lukito Edi Nugroho, Adhi Susanto, Paulus Insap Santosa Leaf Classification Using Shape, Color, and TextureFeatures Department of Electrical Engineering, Gadjah Mada University Yogyakarta, Indonesia.

[3] Maria Rossana C. de Leon, Eugene Rex L. Jalao A Prediction Model Framework for Crop Yield Prediction Southern Luzon State University, Lucban, Quezon, 4328, PHILIPPINES University of the Philippines Diliman, Quezon City, 1101, PHILIPPINES

[4] Doraiswamy, Paul C., et al., “Operational Prediction of Crop Yields Using MODIS Data and Products.” 2007.

[5] SÖKEFELD M., GERHARDS R., OEBEL H., THERBURG R.-D. (2007): Image acquisition for weed detec-tion and identification by digital image analysis. In J.V. Stafford, editor, Precision agriculture volume 6, pages 523–529, The Netherlands, 6th European Conference on Precision Agriculture (ECPA), Wageningen Academic Publishers. ISBN 978-90-8686-024-1

[6] John D.W. Dearnaley Further advances in orchid mycorrhizal John D.W. Dearnaley Faculty of Sciences and Australian Centre for Sustainable Catchments, The University of Southern Queensland,Toowoomba 4350, Australia

[7] Alexandre A. Bernardes, Jonathan G. Rogeri, Roberta B. Oliveira,Norian Marranghello and Aledir S. Pereira Identification of Foliar Diseases in Cotton Crop Universidade Estadual Paulista (UNESP) / Instituto de Biociências, Letras e Ciências Exata (IBILCE), São José do Rio Preto, SãoPaulo, Brasil.

[8] Ernesto Sanz, Noreen von Cramon-Taubadel & David L. Roberts Species differentiation of slipper orchids using color image analysis Departamento de Biología, Facultad de Ciencias, Universidad Autónoma de Madrid, C/Darwin, E-28049 Madrid, Spain.

[9] Martin Weis, Roland Gerhards Detection of weeds using image processing and clustering: Department of Weed Science, University of Hohenheim, Otto-Sander-Straße 5, 70599 Stuttgart, Germany

[10] C.-C. YANG, S.O. PRASHER, J.-A. LANDRY Recognition of weeds with image processing and their use with fuzzy logic for precision farming: Department of Agricultural and Bio systems Engineering and 2Department of Food Science and Agricultural Chemistry, Macdonald Campus of McGill University, Ste-Anne-de-Bellevue, QC, Canada H9X 3V9. Received 18 May 2000; accepted 1 November 200

[11] Kamarul Hawari Ghazali, Mohd. Marzuki Mustafa and Aini Hussain Machine Vision System for Automatic Weeding Strategy using Image Processing Technique : Faculty of Engineering, University Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

[12] Piron; Heijden; Destain, Weed detection in 3D images: Precision Agriculture; Oct2011, Vol. 12 Issue 5, p607

[13] Leafsnap: A Computer Vision System for Automatic Plant Species Identification; Neeraj Kumarl, Peter N. Belhumeur2, Arijit Biswas3, David W. Jacobs3, W. John Kress4, Ida Lopez4, and JO~ao V.B. Soares3; 1. University of Washington, Seattle WA, 2. Columbia University, New York NY, 3. University of Maryland, College Park MD, 4. National Museum of Natural History, Smithsonian Institution, Washington DC