A survey of plant disease detection techniques based on image processing and machine learning

Ravindar Kumar; Vikas Jindal

doi:10.53730/ijhs.v6nS4.10096

Authors

Ravindar Kumar Research Scholar, Department of Computer Science, Chandigarh University, Gharuan, Mohali
Vikas Jindal Professor, Department of Computer Science, Chandigarh University, Gharuan, Mohali

Keywords:

classification, feature extraction, plant disease, segmentation

Abstract

The Plant disease identification is the key which prevent loss and improve quality of the agriculture products. The plant disease detection techniques have various phases which include pre-processing, segmentation, feature extraction and classification. In the pre-processing stage, the contrast of the input image is increased. The points which are not visible are highlighted. The second stage is the segmentation which can help in selecting the region of interest. The feature extraction phase will extract relevant features of the plant. In the last phase, classification algorithm will be applied which can predict name of the disease. The various schemes are already being proposed for the plant disease detection. In this paper, plant disease detection schemes are reviewed in terms of methodologies and outcomes.

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