Abstract:

Nowadays plants are suffering many diseases due to widespread use of pesticides and sprays but identifying rotten areas of plants in the early stage can save plants. Examination of plants disease literally means examining various observable patterns on plants. Manually detecting disease in plants can be a tiresome process, hence image processing can do wonders in this context. Plant disease can be seen in different parts like in stem, root, shoot and even in fruit.

Detection of plant disease by the automatic way not only reduces time but also it is able to save the plant from the disease in the beginning stage itself. We use different image processing techniques to predict the problem in plants. We basically deal with the rose plants and flowers,

we will detect the various kinds of diseases in the rose plants and flowers we will highlight the affected part and classify according to the disease datasets .we are using 4 different datasets, 3 datasets are disease datasets and 1 dataset is healthy plant dataset. Then we will provide the solution for the detected disease which will help the farmer in good cultivation and the more profits.

Objectives:

The basic idea of this project is to build a model which gives the classification of the diseases occuring in the rose plants and give a solution for the diseases occuring in prior without any delay and loss in crop.

We classify the diseases based on the datasets and give a solution related to the diseases to the user. We actually classify based on the symptoms so we can cure it in the early stages.