Survey on Diseased Leaf Using Segmentation
| Autor: | K. Joseph Abraham Sundar, N. Jothiaruna |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Artificial neural network
business.industry Computer science 04 agricultural and veterinary sciences 02 engineering and technology Color space Machine learning computer.software_genre Transformation (function) Region growing 040103 agronomy & agriculture 0202 electrical engineering electronic engineering information engineering 0401 agriculture forestry and fisheries Preprocessor 020201 artificial intelligence & image processing Segmentation Artificial intelligence business Focus (optics) computer |
| Zdroj: | 2019 International Conference on Intelligent Sustainable Systems (ICISS). |
| DOI: | 10.1109/iss1.2019.8908017 |
| Popis: | Agriculture plays a vital role in all living things but it has many challenges to cultivate something like plants and vegetables from diseases. Disease affecting in the plant or leaf is quite a natural, if proper care is taken or not taken plant will surely affect by the disease because of nature, climate, soil condition and also by water. Here, we mainly focus on the detection of a diseased leaf. To solve those challenges many techniques are used like Color space transformation, Neural Network, Preprocessing, Classification, Segmentation, and Extraction techniques are used. Any techniques can be used to detect disease from the leaf, but finding which can give the better solution from those techniques is hard because some techniques can give better result some may give low accuracy. In this paper, we mainly focus on Color Space transformation, Neural Network, Segmentation has many algorithms like region growing method and Morphological operation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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