Methodology

For our evaluation (Sankaran, Mishra, Ehsani, & Davis, 2010) as on this, we concentrated only on one plant, tomato. Thus, distinct diseases display exceptional variations, which include shade, shape and illumination in light. In this paper, images have been taken to pick out diseases based on the signs that differentiate one plant from another (Kannan, Prashanth, & Maliyekkal, 2020). The current advancement in the field of machine learning and computer vision requires distinctive features to generate accurate inference. The images used in this work are taken from the internet similar to distinctive types of tomato plants as given in Figure 13.5.

The major steps involved in the feature extraction process of tomato leaf images are image acquisition, image pre-processing, segmentation, feature extraction and disease identification as shown in Figure 13.6.