A Survey on Plant Disease Detection using Support Vector Machine

• Published in: 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT) pp. 292 - 295
• Main Authors: Poojary, Harshitha, Shabari, Shedthi B.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-03-2018
• Subjects: Accurate; Acquisition; Agriculture; Clustering algorithms; Diseases; Feature extraction; Image color analysis; Image segmentation; Segmentation; Support Vector Machine; Support vector machines
• DOI: 10.1109/ICCPCCT.2018.8574314

Agriculture is an important source of livelihood and Indian economy depends on agricultural production. It is important to detect the plant leaf diseases at early stage to increase the crop yield and profit. Image processing technique is used to detect the leaf diseases accurately since naked eye observation of the diseases does not provide accurate result all the time especially during the early stage. It was done in five phases which are image acquisition, preprocessing of the acquired image, feature extraction, classification of the diseases and displaying the result. This paper provides a detailed survey about classification of the agricultural diseases by using Support Vector Machine classifier.