Hey Guys,
We are designing the solution to detect the diseased part of cotton leaves and plants by finding the optimum way with minimum cost. Agricultural productivity is something on which the Economy highly depends. This is one of the reasons that disease detection in plants plays an important role in the agriculture field, as having the disease in plants is quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity, or productivity is affected.
PROBLEM STATEMENT:
As we all know that Indian economy depends on agriculture but leaf
infection phenomena cause the loss of major crops results in economic loss. Leaf infection is the invasion of leaf tissues by disease-causing agents such as bacteria,
virus, fungus, etc leading to degradation of the leaf as well as plant. This can be characterized
by spots on the leaves, dryness of leaves, color change in leaves, and defoliation. Automatic detection of plant diseases is an
essential research topic as it may prove benefits in monitoring large fields of crops, and thus
automatically detect the symptoms of diseases as soon as they appear on plant leaves. The proposed system is a software solution for the automatic detection and classification of plant leaf disease.
PROPOSED SOLUTION:
may prove a benefit in monitoring large fields of crop and thus
automatically detects the symptoms of a disease as they appear on the plant leaves. As the disease can be identified and the solution to the disease can be found. This information is sent to the farmer through GSM Modem.
It also covers a survey on different disease classification
techniques that can be used for plant leaves detection. Image segmentation, which is an important aspect of disease detection in plant leaf disease.
FEATURES:
➢ To detect the unhealthy regions of plant leaves.
➢ Classification of plant leaf disease using texture features.
➢ Coding is used to analyze leaf infection.
➢ The analyzed information/ result is sent via SMS to farmers.
➢ Plant disease identification by the visual way is a more laborious task and at
the same time, less accurate and can be done only in limited areas.
➢ Automatic detection of the diseases by just seeing the symptoms on the
plant leaves makes it easier as well as cheaper. This also supports
machine vision to provide image-based automatic process control.