• Miss Neha Gopalrao Kurale
• Mr. Jadhav Santosh B.
• Miss Nishigandha Gopalrao Kurale

Leaf diseases are the disorder, issues that affect the plants. In this paper, the problem of leaf dis- eases like the difficulties encountered while classifying the diseases in agriculture can be solved or reduce. In this paper, we propose features extraction techniques for classification of leafdisease. A combination of Tex- ture, Shape Feature and Pixel value are developed for classifying the images of leaf diseases. The proposed system can classify leaf images automatically as normal, image, affected. The proposed framework contains four steps. In the first step, the images are pre-processed. In the second step, the images are segmented by Thresholding and Edge Detection. In the third step, the texture, shape and pixel value are calculated using the Gray Level Co-occurrence Matrix, Moment Invariant and Walsh Hadamard Transform are computed over the segmented image and combined to form the single descriptor. In the final step, the K-NN, Multiclass- SVM and Decision Tree classifiers are used for classification of leaf images. The total datasets contain 5000 images, 1000 images of each disease like the Normal, affected, Anthracnose, wilt and Bacterial blight. The 2800 images are used for Training and 1200 images are used for Testing. The classification accuracy for Deci- sion Tree is 89.5%, Neural Network 91.70%, SVM is 90.70%, K-NN 96.90%. The K-NN classifier can be used for classifying the images and also reduces time as compare to the other classifiers.

Image processing, SVM, KNN, Neural Network, leaf disease.

"Leaf Disease Detection Using Image Processing Techniques - The Study.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.268-280, April-2019, Available :http://www.jetir.org/papers/JETIR1904N43.pdf

"Leaf Disease Detection Using Image Processing Techniques - The Study.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp268-280, April-2019, Available at : http://www.jetir.org/papers/JETIR1904N43.pdf