عنوان مقاله :
ﺗﺸﺨﯿﺺ و ﺗﻌﯿﯿﻦ ﺷﺪت ﺑﯿﻤﺎري ﺳﻔﯿﺪك داﺧﻠﯽ ﺑﺮگﻫﺎي ﺧﯿﺎر ﮔﻠﺨﺎﻧﻪاي ﺑﻪروش ﭘﺮدازش ﺗﺼﻮﯾﺮ
عنوان به زبان ديگر :
Detecting and Severity Measurement of Downy Mildew Disease in Greenhouse Cucumber Leaves Using Image Processing Technique
پديد آورندگان :
ﻣﺤﻤﺪي ﮔﻞ، رﺿﺎ داﻧﺸﮕﺎه اراك - داﻧﺸﮑﺪه ﮐﺸﺎورزي - ﮔﺮوه آﻣﻮزﺷﯽ ﻣﻬﻨﺪﺳﯽ ﻣﮑﺎﻧﯿﮏ ﺑﯿﻮﺳﯿﺴﺘﻢ , ﺑﺨﺸﯽ ﭘﻮر زﯾﺎرﺗﮕﺎﻫﯽ، ﻋﺎدل داﻧﺸﮕﺎه شيراز - داﻧﺸﮑﺪه ﮐﺸﺎورزي - ﮔﺮوه آﻣﻮزﺷﯽ ﻣﻬﻨﺪﺳﯽ ﻣﮑﺎﻧﯿﮏ ﺑﯿﻮﺳﯿﺴﺘﻢ
كليدواژه :
آﻧﺎﻟﯿﺰ ﺗﺸﺨﯿﺼﯽ , ﭘﺮدازش ﺗﺼﻮﯾﺮ , ﺧﯿﺎر ﮔﻠﺨﺎﻧﻪ اي , ﺳﻔﯿﺪك داﺧﻠﯽ
چكيده فارسي :
ﺳﻔﯿﺪك داﺧﻠﯽ ﮐﺪوﺋﯿﺎن ﯾﮑﯽ از ﺑﯿﻤﺎريﻫﺎي ﻣﻬﻢ ﺧﯿﺎر در ﻣﻨﺎﻃﻖ ﻣﺮﻃﻮب و ﮔﻠﺨﺎﻧﻪﻫﺎ ﻣﺤﺴﻮب ﻣﯽﺷﻮد و اﮔﺮ ﺑﻪ ﻣﻮﻗﻊ ﺗﺸﺨﯿﺺ داده ﻧﺸﻮد، ﻣﯽﺗﻮاﻧﺪ ﻣﻨﺠﺮ ﺑﻪ ﺧﺴﺎرتﻫﺎي ﺷﺪﯾﺪي ﺑﻪ ﮐﻤﯿﺖ و ﮐﯿﻔﯿﺖ ﻣﺤﺼﻮل ﺷﻮد. در اﯾﻦ ﭘﮋوﻫﺶ، اﻣﮑﺎن اﺳﺘﻔﺎده از روش ﺗﺤﻠﯿﻞ ﺗﺼﻮﯾﺮ در ﺗﻌﯿﯿﻦ ﺑﯿﻤﺎري ﺳﻔﯿﺪك داﺧﻠﯽ ﺧﯿﺎر ﮔﻠﺨﺎﻧﻪاي ﻣﻮرد ﺑﺮرﺳﯽ ﻗﺮار ﮔﺮﻓﺖ. ﺗﺼﺎوﯾﺮ از ﺑﺮگ ﮔﯿﺎﻫﺎن آﻟﻮده در ﻣﺮاﺣﻞ ﻣﺨﺘﻠﻒ اﺑﺘﻼ ﺑﻪ ﺑﯿﻤﺎري ﺗﻬﯿﻪ ﺷﺪﻧﺪ و ﺟﻬﺖ ﭘﺮدازش در ﺟﻌﺒﻪ اﺑﺰار ﭘﺮدازش ﺗﺼﻮﯾﺮ ﻧﺮم اﻓﺰار ﻣﺘﻠﺐ ﭘﺮدازش ﺷﺪﻧﺪ. ﺗﺼﺎوﯾﺮ رﻧﮕﯽ ﺑﻪ ﻓﻀﺎﻫﺎي رﻧﮕﯽ ﻣﺨﺘﻠﻒ اﻧﺘﻘﺎل داده ﺷﺪﻧﺪ و ﻣﺆﻟﻔﻪﻫﺎي رﻧﮕﯽ ﺗﻮﺳﻂ آﻧﺎﻟﯿﺰ ﺗﺸﺨﯿﺼﯽ ﻣﻮرد ﺑﺮرﺳﯽ ﻗﺮار ﮔﺮﻓﺘﻨﺪ. ﻣﺆﻟﻔﻪ رﻧﮕﯽ Cr ﺑﺮاي ﺗﺸﺨﯿﺺ ﻟﮑﻪﻫﺎي ﺑﯿﻤﺎري ﻣﻨﺎﺳﺐ ﺗﺸﺨﯿﺺ داده ﺷﺪ و ﺑﺮاي ﺗﻮﺳﻌﻪ اﻟﮕﻮرﯾﺘﻢ ﻣﻮرد اﺳﺘﻔﺎده ﻗﺮار ﮔﺮﻓﺖ. دﻗﺖ اﻟﮕﻮرﯾﺘﻢ ﺗﺸﺨﯿﺼﯽ در ﺷﻨﺎﺳﺎﯾﯽ ﻧﻘﺎط آﻟﻮده ﺑﺮگ ﺑﺮاﺑﺮ ﺑﺎ 1/4±97/4 درﺻﺪ ﺑﻮد. ﺑﺮاي ﻃﺒﻘﻪﺑﻨﺪي ﺷﺪت ﺑﯿﻤﺎري ﻧﯿﺰ از آﻧﺎﻟﯿﺰ ﺗﺸﺨﯿﺼﯽ اﺳﺘﻔﺎده ﺷﺪ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن دادﻧﺪ ﮐﻪ ﭘﺮدازش ﺗﺼﻮﯾﺮ روﺷﯽ ﻣﻨﺎﺳﺐ ﺑﺮاي ﺗﺸﺨﯿﺺ دﻗﯿﻖ ﺑﯿﻤﺎري ﺳﻔﯿﺪك داﺧﻠﯽ ﺑﺮگ ﺧﯿﺎر ﮔﻠﺨﺎﻧﻪاي اﺳﺖ. ﻫﻢﭼﻨﯿﻦ آﻧﺎﻟﯿﺰ ﺗﺸﺨﯿﺼﯽ اﺑﺰار ﻣﻨﺎﺳﺒﯽ ﺑﺮاي ﻃﺒﻘﻪﺑﻨﺪي ﺷﺪت ﺑﯿﻤﺎري در ﺗﺼﺎوﯾﺮ ﻣﻨﺘﺠﻪ از ﭘﺮدازش ﺗﺼﻮﯾﺮ ﻣﯽﺑﺎﺷﺪ.
چكيده لاتين :
Downy Mildew of cucurbits is one of the most important diseases of cucumber in humid areas and greenhouses. It can lead to significant damages to the quality and quantity of the product, if not diagnosed on time. In this study, the possibility of using image processing for determining the downy mildew of greenhouse cucumber was investigated. The captured images from cucumber leaves at several stages of disease severity were processed in Image Processing toolbox of MATLAB programming software. Color images were transferred to several color spaces and then color components were examined by discriminant analysis. Cr color component was determined to be suitable to detect disease spots in leaf and was used to develop the recognition algorithm. The accuracy of algorithm in terms of identify the infected areas of leaves was 97.4±1.4 percent. Discriminant analysis was also used to classify the severity of the disease. Results revealed that image processing is a suitable method for accurate diagnosis of downy mildew in greenhouse cucumber leaves. Discriminant analysis is also a useful tool to classify disease severity in images resulted from image processing.
عنوان نشريه :
مكانيزاسيون كشاورزي
عنوان نشريه :
مكانيزاسيون كشاورزي