A Review on Detection of Plant Diseases u Image Processing Technique

Identification of the plant diseases is the preventing the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the studies of visually observable patterns seen on the plant. Health monitoring and disease detection on plant is very critical for sustainable agriculture. It is very difficult to monitor the plant diseases manually requires tremendous amount of work, expertize in the plant diseases, and also require the excessive processing time. Hence, image processing is used for the detection of plant diseases. Disease detection involves the steps like image segmentation, feature extraction and classification. This paper discussed the method used for the detection of plant diseases using their leaves images. Agriculture is a most important and ancient oc in India. As economy of India is based on agricultural production, utmost care of food production is necessary. Pests like virus, fungus and bacteria causes infection to plants with loss in quality and quantity production. There is large amount of loss of farmer in production. Hence proper care of plants is necessary for same.


Introduction
India is a cultivated country and from ancient times all the population depends on the agriculture. There diversity in selection of various plants and crops and there are many pesticides available for each and every plants. Diseases  Identification of the plant diseases is the key to preventing the losses in the yield and quantity of the agricultural product. The studies of the plant diseases mean the studies of visually observable patterns seen on the plant. Health monitoring and disease detection on able agriculture. It is very difficult to monitor the plant diseases manually requires tremendous amount of work, expertize in the plant diseases, and also require the excessive processing time. Hence, image processing is used for the detection of seases. Disease detection involves the steps like image segmentation, feature extraction and classification. This paper discussed the method used for the detection of Agriculture is a most important and ancient occupation in India. As economy of India is based on agricultural production, utmost care of food production is necessary. Pests like virus, fungus and bacteria causes infection to plants with loss in quality and quantity production. There loss of farmer in production. Hence proper care of plants is necessary for same.

Image processing, Plant Diseases,
India is a cultivated country and from ancient times all the population depends on the agriculture. There exists diversity in selection of various plants and crops and there are many pesticides available for each and every plants. Diseases

B. Feature Extraction
Feature Extraction is an important part in the disease detection. It plays an important role in identification of an object. Feature extraction is used in many applications in image processing. Color, texture edges, morphology are the features which are used in disease detection.
Monica jhuria et al took color, morphology, texture as feature for the disease detection. It is found that morphological result gives more result than any other features. Texture shows how the color is distributed in the image, hardness of the image.
In Feature Extraction here we are using Haar algorithm, which first extract the feature of image and after the whole implementation of process it stores the new image on server and extract features from transformed server. Haar wavelets as the basis of transformation functions. Haar wavelet transformation is composed of a sequence of low pass and high pass filters, known as filter bank.

Haar Algorithm
Read pixels of image

C. Detection and Classification of Plant Diseases
The final stage is the detection of the diseases and with the help of disease classify the plants with the disease matches with the given dataset. For the disease detection and classification, we are implementing the deep learning algorithm.
Deep learning algorithm is used to classify the specified image into appropriate disease hence it will be easy to detect the disease and find out the remedy over the disease.

III. Deep learning algorithm
In the deep learning algorithm detection and classification can be done. Here one image is given the algorithm read the vector matrix of image that is features of image. After the vector matrix the extracted features matches with the trained dataset containing the disease wise features. In the dataset match the extracted disease with the given diseases i.e. fetch matching diseases. After that calculate how many links are matching with the extracted image. Here suppose Z be the weight of the diseases. Z gives the similarities between the image features and the trained data set.
The activation function used to filter out the disease using the activation function value. The activation function value is calculated as follows: Deep learning is layered algorithm, when output of first layer is calculated then the output is transferred to the next layer, again in the next level calculate the activation function value. Repeat the same procedure for each layer until the output reduces to one or two disease.

IV. Advantages
1. Efficient and user friendly system 2. Improved accuracy with the help of Haar Algorithm and Deep learning algorithm 3. Increased layers of deep learning algorithm to get most accurate and appropriate result.

CONCLUSION
For successful cure of the plant and crops it is necessary to detect plant diseases accurately. Hence from above discussion it is proved that image processing technique is useful in detection. By using this technique, we can properly classify and identify the diseases. Haar wavelet transform is used for proper classification of images and deep learning algorithm is used for accuracy. Hence it is proved that these techniques are applicable for the detection of diseases.