A Survey on Cluster Analysis Techniques for Plant Disease Diagnosis

International Journal of Computer Science and Engineering

© 2016 by SSRG - IJCSE Journal

Volume 3 Issue 6

Year of Publication : 2016

Authors : T.Nagarathinam, Dr. K. Rameshkumar

10.14445/23488387/IJCSE-V3I6P103

How to Cite?

T.Nagarathinam, Dr. K. Rameshkumar, "A Survey on Cluster Analysis Techniques for Plant Disease Diagnosis," SSRG International Journal of Computer Science and Engineering , vol. 3,  no. 6, pp. 11-17 , 2016. Crossref, https://doi.org/10.14445/23488387/IJCSE-V3I6P103

Abstract:

Plants are one of the major key resources to crack the trouble of global warming in the world. But plant diseases like Blast, canker, Bacterial Leaf Blight; Rice tungro, black spot, Scab, Powdery, Downey, mildew, Speckle, early scorch ashen mold, tiny whiteness, cotton mold, late scorch and etc., stops the growth of the plants. If the diseases are not detected in the early hours then there are decreases in the production of plantation. In this paper we surveyed Cluster Analysis technique for plants diseases detection and diagnosis.

Keywords:

ANN, Brown sport, fuzzy C-means, kmean, Leaf Blast..

References:

[1] Di Cui, Oin Zhang, Minzan Li, Youfu Zhao and Glen L. Hartman[2009] Detection of soybean rust using a multispectral image sensor, SpringerLink –Journal article.
[2] Dheeb Al Bashish, Malik Braik, and Sulieman Bani- Ahmad ,”A Framework for Detection and Classification of Plant Leaf and Stem Diseases”, 2010 International Conference on Signal and Image Processing.
[3] H. Al-Hiary, S. Bani-Ahmad et al, Fast and Accurate Detection and Classification of Plant Diseases, International Journal of Computer Applications (0975 – 8887) Volume 17– No.1, March 2011
[4] Toran Verma, Susanta Kumar Satpathy-“A Step towards Precision Farming of Rice Crop by Estimating Loss Caused by Leaf Blast Disease Using Digital Image Processing and Fuzzy Clustering”, International Journal of Computer Trends and Technology- May to June Issue 2011.
[5] R. L. Pugoy and V. Y. Mariano "Automated rice leaf disease detection using color image analysis", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), (July 08, 2011)
[6] Sekulska-Nalewajko J, Goclawski J.” A semi-automatic method for the discrimination of diseased regions in detached leaf images using fuzzy c-means clustering”, 7th international conference on perspective technologies and methods in MEMS design. Polyana-Svalyava: IEEE; 2011. pp. 172–175.
[7] Jayamala K. Patil, Raj Kumar- “Color Feature Extraction of Tomato Leaf Diseases”, International Journal of Engineering Trends and Technology- Volume2Issue2- 2011. ISSN: 2231-5381 http://www.internationaljournalssrg.org Page 72.
[8] Sannakki S.S., Rajpurohit V.S., Nargund V.B., Arun Kumar R.and Yallur P.S.,” A Hybrid Intelligent System for Automated Pomegranate Disease detection and Grading”, International Journal of Machine Intelligence ISSN: 0975– 2927. 2011.
[9] Tushar H Jaware, Ravindra D Badgujar and Prashant G Patil,” Crop disease detection using image segmentation”, Proceedings of Conference on Advances in Communication and Computing (NCACC'12)”, April 21, 2012.
[10] N.Valliammal and Dr.S.N.Geethalakshmi.,”Leaf Image Segmentation Based On the Combination of Wavelet Transform and K Means Clustering”, (IJARAI) International Journal of Advanced Research in Artificial Intelligence, Vol. 1, No. 3, 2012
[11] Dheeb Al Bashish, Malik Braik, and Sulieman Bani- Ahmad, “A Framework for Detection and Classification of Plant leaf and Stem Diseases”, 2012 International conference on signal and Image Processing, pg.no.113- 118, Chennai, India
[12] Wang H, Li G, Ma Z, Li X. “Application of neural networks to image recognition of plant diseases”, Proceedings of the 2012 International Conference on Systems and Informatics (ICSAI) Yantai: IEEE; 2012.; pp. 2159–2164.
[13] Jagadeesh Devdas Pujari1, Rajesh et al, Grading and Classification of Anthracnose Fungal Disease of Fruits based on Statistical Texture Features, International Journal of Advanced Science and Technology Vol. 52, March, 2013
[14] Jagadeesh D. Pujari, Rajesh Yakkundimath and Abdulmunaf S. Byadgi. “Classification of Fungal Disease Symptoms affected on Cereals using Color Texture Features”, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.6, No.6 (2013), pp.321-330 http://dx.doi.org/10.14257/ijsip.2013.6.29 . ISSN: 2005- 4254 IJSIP.
[15] Al-Tarawneh, Mokhled S. "An Empirical Investigation of Olive Leave Spot Disease Using Auto-Cropping Segmentation and Fuzzy C-Means Classification." World Applied Sciences Journal 23.9 (2013).
[16] Vivek Chaudhari,C.Y. Patil, “Disease detection of cotton leaves using advanced image processing”, International journal of advanced computer research, June-2014 (ISSN (print): 2249-7277 ISSN (online): 2277-7970) Volume-4 Number-2 Issue-15,pg 653-659,June-2014.
[17] Niket Amoda, Bharat Jadhav, Smeeta Naikwadi. “Detection and Classification of Plant Diseases using Image Processing”, International Journal of Innovative Science, Engineering and Technology 2014;1- 7.
[18] Rastogi, A.; Arora, R.; Sharma, S., "Leaf disease detection and grading using computer vision technology & fuzzy logic," in Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference, vol., no., pp.500-505, 19-20 Feb. 2015.
[19] Amit Kumar Singh, Rubiya .A, B.Senthil Raja- “ Classification of Rice disease using digital image processing and SVM Classifier”, International Journal of Electrical and Electronics Engineers ISSN- 2321-2055 (E) http://www.arresearchpublication.com IJEEE, Volume 07, Issue 01, Jan- June 2015.
[20] Nikita Rishi, Jagbir Singh Gill- “An Overview on Detection and Classification of Plant Diseases in Image Processing”, International Journal of Scientific Engineering and Research (IJSER) www.ijser.in ISSN (Online): 2347-3878, Impact Factor (2014): 3.05 Volume 3 Issue 5, May 2015.
[21] Megha P Arakeri, Malavika Arun, Padmini R K “ Analysis of Late Blight Disease in Tomato Leaf Using Image Processing Techniques”, I.J. Engineering and Manufacturing, 2015, 4, 12-22 Published Online November 2015 DOI: 10.5815/ijem.2015.04.02 Available online at http://www.mecs-press.net/ijem.
[22] Bed Prakash , Amit Yerpude – “ Identification of Mango Leaf Disease and Control Prediction using Image Processing and Neural Network”, IJSRD - International Journal for Scientific Research & Development/ Vol. 3, Issue 05, 2015 | ISSN (online): 2321-0613.