Fungal Genomics & Biology
Open Access

Department of Biosystems Engineering, Takestan Branch, Islamic Azad University, Takestan, Iran

Publications

• Research   
  Identify Fungal Diseases of Cucumber (Powdery Mildew and Anthracnose) Using Image Processing and Artificial Neural Network Approach
  Author(s): Hadi Hosseini, Davood Mohammad Zamani, Seyed Mohamad Javidan* and Abbas Arbab
  
  Plant disease can cause reduce quality and quantity of agriculture crops. In some countries farmers spend considerable time to consult with plant protection, while the time is an important factor to controlling of disease. Due to the fact that Powdery Mildew and Anthracnose fungal diseases cause the most damage in cucumber greenhouses, in this study, by presenting a non-destructive method based on image processing technique and artificial neural network, these two types of fungal diseases have been diagnosed. The steps related to the implementation of the proposed method are divided into three parts: Segmentation, separation of damaged parts from the leaf and classification of the disease type class. After color and texture features were extracted from cucumber leaf samples, a multilayer perceptron neural network with error post-diffusion learning algorithm was us.. View More»
  DOI: 10.35248/2165-8056.23.13.232

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