• Manpreet Kaur
• Lal Chand

Agriculture in now days is not just a mean to feed population, it is more than that especially in countries like India where economy is directly or indirectly affected by production. So to maintain economical status, plants should be free from disease. Thus detection of disease in plants should be of great concern. To detect disease in plants number of techniques of segmentation and classifications are applied. Proposed work in paper begins with preprocessing of input plant image. Then processed image is segmented with k-mean clustering and thresholding, after getting clusters features are extracted using GLCM. GLCM (Gray Level Concurrence Matrix) is used to extract texture related features from plat images. At last classification is performed using Support Vector Machine that shows more accurate results for identification and detection of plant leaves diseases.

Segmentation, GLCM, SVM, plant disease detection.

"Detection Of Diseased Plant Leaf Images Using SVM Classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.492-497, August-2018, Available :http://www.jetir.org/papers/JETIR1808972.pdf

"Detection Of Diseased Plant Leaf Images Using SVM Classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp492-497, August-2018, Available at : http://www.jetir.org/papers/JETIR1808972.pdf