Scab Diseases Detection of Potato using Image Processing
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - Issue 2012 by IJCTT Journal|
|Volume-3 Issue-1 |
|Year of Publication : 2012|
|Authors :Debabrata Samanta, Prajna Paramita Chaudhury, Arya Ghosh.|
Debabrata Samanta, Prajna Paramita Chaudhury, Arya Ghosh."Scab Diseases Detection of Potato using Image Processing"International Journal of Computer Trends and Technology (IJCTT),V3(1):97-101 Issue 2012 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract: - -Scab disease of potato tubers resulting in lowered tuber quality due to scab-like surface lesions. Potato is the most demanding vegetable of India to increase the productivity. In this paper proposes image processing methodology to detect scab disease of potato. In this paper first, the captured images are collected from different potato field and are processed for enhancement. Then image segmentation is carried out to get target regions (disease spots). Finally, analysis of the target regions (disease spots) based on histogram approach to finding the phase of the disease and then the treatment consultative module can be prepared by on the lookout for agricultural experts, so plateful the farmers.
 WANG Chenglong, LI Xiaoyu, WANG Wei, Liu Jie, TAO Hailong and WEN Dongdong , “Detection of potato’s size based on centroidal principal axis” , African Journal of Agricultural Research Vol. 6(17), pp. 4140-4148, 5 September, 2011.
 Ebrahim Ebrahimi, Kaveh Mollazade, Arman Arefi , “Detection of red ripe tomatoes on stem using Image Processing Techniques” , Journal of American Science, 2011;7(7)
 Miller W M, Drouillard G. P. Multiple feature analysis for machine vision grading of Florida citrus. Applied Eng Agri,2001; 17(5): 627-633.
 Aleixos N, Blasco J, Navarron F, Molto E. Multispectral inspection of citrus in real-time using machine vision and digital signal processors. Comput. Electron Agri, 2002; 33(2): 121-137.
 Blasco J, Aleixos N, Gomez J, Molto E. Citrus sorting by identification of the most common defects using multispectral computer vision. J Food Eng, 2007; 83(3): 384-393.
Keywords— Image processing, disease detection, image learning technique.