Plant Leaf Disease Detection
An analysis of various methods for detecting image processing plant leaf diseases and how the denoising step can be achieved by application of different filters is presented.
Abstract
— Plant leaf disease detection plays an important role in the field of agriculture. Early detection of the disease can prevent the loss of formers and help in the increasing the productivity of the crop. Diseases can be detected by different image processing and machine learning algorithms and pattern recognition. It is not a simple task to manually observe and classify leaf diseases, since it requires a lot of time, resources, commitment, etc. So, with an automated image processing and machine learning system, it's easier to identify diseases. Plant leaf disease detection consist of five basic steps; image acquisition, preprocessing, segmentation, feature extraction and classification. the denoising step can be achieved by application of different filters. This paper presents an analysis of various methods for detecting image processing plant leaf diseases.