Detection of foliar diseases using image processing techniques 1

In addition to his, infections caused by this disease cause premature ripening of the fruit (Juárez-Becerra et al., 2010). [...]detecting these symptoms in plants in an efficient manner, has become an important factor in the maintenance of crops, allowing the farmer to reduce the risk of diseases and sustain production and quality in their crops (Finagro, 2014). In this way, the farmer has the opportunity to prevent the spread of different diseases in the crop (Sankaran et al., 2010; AlHiary et al, 2011). [...]in this work, it is proposed to use digital image processing techniques to detect the percentage of affected area of the disease Phytophthora infestans in tomato plants. [...]we have the analysis of thresholding by color for the segmentation of the background and the disease. [...]machine learning techniques have been implemented where characteristics of color spaces are extracted, such as RGB, HSV and LAB to segment, train and classify the different types of diseases that occur in plants (Huang, 2007; Meunkaewjinda et al., 2008; Wiwart et al., 2009; Baghel & Jain, 2016; Patel & Dewangan, 2017).