Abstract: Plant disease detection is an Innovative and Enlightening System helping the users to know the disease, trainings or any interesting things taking place around their Area. This Organization aids the native community to keep themselves up to date about the events around their locality or zone or in their town. There are 2 things for this method to work; one for the image processing and another is machine learning.
Modern approaches such as machine learning and deep learning algorithm have been employed to increase the recognition rate and the accuracy of the results. Random forests are as a whole, learning method for classification, regression and other tasks that operate by constructing a forest of the decision trees during the training time. Unlike decision trees, Random forests overcome the disadvantage of over fitting of their training data set and it handles both numeric and categorical data.
The histogram of oriented gradients (HOG) is an element descriptor utilized as a part of PC vision and image processing for the sake of object detection. Here we are making utilization of three component descriptors:
Keywords: Machine Learning, Image processing, Random Forests, HOG, Object detection, Histogram graph
| DOI: 10.17148/IJARCCE.2022.111130