Author : V.Gayathri 1
Date of Publication :22nd March 2018
Abstract: In rural field loss of yield for the most part happens because of broad of ailment. Generally the discovery and recognizable proof of the ailment is seen when the ailment advances to extreme stage. The framework is proposed to recognize and characterize the infections in leaf utilizing the picture handling procedures beginning from picture securing, pre-preparing, preparing and testing. . Picture handling strategies for this sort of choice examination includes preprocessing, highlight extraction and characterization arrange. At Processing, an info picture will be resized and area of intrigue choice performed if necessary. Here, shading and surface highlights are extricated from a contribution for arrange preparing and order. Shading highlights like mean, standard deviation of HSV shading space and surface highlights like vitality, complexity, homogeneity and relationship. . Highlights are extricated by the GLCM. BPN-FF classifier will be utilized for arrangement in view of learning with the preparation tests and along these lines giving the data on the irregularity (Early leaf spot, late leaf spot). The framework will be utilized to characterize the test pictures naturally to choose leaf either variation from the norm or great one
Reference :
-
- Ghaiwat Savita N, Arora Parul. Detection and classification of plant leaf diseases using image processing techniques: a review. Int J Recent Adv Eng Technol2014;2(3):2347–812. ISSN (Online).
- Dhaygude Sanjay B, Kumbhar Nitin P. Agricultural plant leaf disease detection using image processing. Int J Adv Res Electr Electron Instrum Eng 2013;2(1).
- Mrunalini R Badnakhe, Deshmukh Prashant R. An application of K-means clustering and artificial intelligence in pattern recognition for crop diseases. Int Conf Adv Inf Technol 2011;20201IPCT.
- Arivazhagan S, Newlin Shebiah R, Ananthi S, Vishnu Varthini S.Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features. Agric Eng Int CIGR2013;15(1):211–7.
- Kulkarni Anand H, Ashwin Patil RK. Applying image processing technique to detect plant diseases. Int J Mod Eng Res 2012;2(5):1–4.
- Bashir Sabah, Sharma Navdeep. Remote area plant disease detection using image processing. IOSR J Electron Commun Eng 2012;2(6):31– 4. ISSN: 2278- 2834.
- Chaudhary Piyush et al. Color transform based approach for disease spot detection on plant leaf. Int Comput Sci Telecommun 2012;3(6)
- Rathod Arti N, Tanawal Bhavesh, Shah Vatsal. Image processing techniques for detection of leaf disease. Int J Adv Res Comput Sci Softw Eng 2013;3(11).
- Beucher S, Meyer F. The morphological approach to segmentation: the watershed transforms. In: Dougherty ER, editor. Mathematical morphology image processing, vol.New York: Marcel Dekker; 1993. p. 433–81.
- Bhanu B, Lee S, Ming J. Adaptive image segmentation using a genetic algorithm. IEEE Trans Syst Man Cybern Dec1995;25:1543–67.