Leaves Diseases Detection of Tomato Using Image Processing

Today's era is an era of Scientific Development. Where, technologies and new ways of solving real-life problems are being invented every day. With the increasing population of the world, basic need of food is increasing parallelly. That's why agriculture plays an important role all over the world. Throughout the year different crops, vegetables, fruits, fishes, animals are cultivated to fulfill the need of people as well as to gain profit for the people involving in those cultivation. But due to lack of proper cultivating knowledge, experience and sense of disease prediction, sometimes those cultivating crops and grains get damaged partially or even completely. Of course, that ends up with a huge loss for the farmers as well as for the economic growth of the country. So, this research paper tends to merge or combine a part of agricultural sector with science and technology to reduce the loss caused by insect's attack and diseases of plant leaves. More specifically, this research happens to combine agricultural sector with computer science. Since, agriculture is a vast sector to work on, to simplify the work, we are detecting vegetable plant diseases using Artificial Intelligence and computer science. To implement this idea, we have chosen “Tomato” as the core vegetable which's leaf diseases are to be predicted by using the algorithms of Artificial Intelligence, CNN and computer science. Tomato is a very popular vegetable in our country as well as in the world, the main motive is to solve the diseases detection problems that the “Tomato” growers are facing nowadays in their cultivable land especially in Bangladesh. And that is why we have chosen tomatoes leaf diseases prediction which is very important. This research tried to eradicate the harmful side effects of chemicals and pesticides with the help of Image Processing system. In this research 6 classification of tomato leaves disease have been detected including one healthy class. The farmers can input the symptoms in the form of images of affected tomato leaves and it will predict the diseases. The system showed up an accuracy over 96.55% at the end. It is counted as a user-friendly system that will help the vegetable farmers specially the “Tomato” growers to reduce insect suppression by detecting its leaf diseases and increase the yield by creating more opportunities for various vegetable diseases research and professional market place.