ISSN: 2165-8056
+44 1223 790975
Department of Biosystems Engineering, Takestan Branch, Islamic Azad University, Takestan, Iran
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