Fungus/Disease Analysis in Tomato Crop using Image Processing Techniques
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2014 by IJCTT Journal | ||
| Volume-13 Number-2 |
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| Year of Publication : 2014 | ||
| Authors : Shruti , Nidhi Seth | ||
| DOI : 10.14445/22312803/IJCTT-V13P113 |
Shruti , Nidhi Seth. "Fungus/Disease Analysis in Tomato Crop using Image Processing Techniques". International Journal of Computer Trends and Technology (IJCTT) V13(2):61-63, July 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
The crop of tomato is very often infected by a disease that leaves spots of brown, gray or off-white colors on the plant’s leafs in winter. Scientifically, this disease is known as cercospora leaf spot or cercospora cruciferarum. It’s a kind of fungus that often kills young seedlings. The fungus spreads by air and can also infect tomato plants. Therefore, it is important to monitor the leaf at regular intervals so as to keep track on quality of growing tomato crop. In the presented paper, a novel machine vision system has been proposed that visual inspects the leafs coming out of the soil and based on spots on leaves, it determines the nature of fungus and its depth into the tomato steam. The size of the fungus, color depth and location and locus of the fungus on leaves give an accurate determination of crop quality under the soil. In the presented thesis work, the image of the crop leaves are taken by a good quality color camera and processed for getting a gray colored and segmented image depending upon the nature and size of the fungus. A criterion is set for acceptable and rejects crop quality based on the fungus level.
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Keywords
Segmentation, K-Means, Pixel Neighborhood