<![CDATA[In the field of agriculture, prevention and control of plant disease are very important. The diseases can be controlled at an early stage by rapid and accurate diagnostics of the same, which could help control the disease at its initial stage. The automatic technique for plant disease detection helps reduce the need for meticulous individual plant monitoring on the farm. A combination of machine learning and image processing may help in plant disease recognition. The proposed technique is based on a combination of the abovementioned techniques, where for extracting leaf image features such as color, texture, and intensity, the G Gabor filter and watershed segmentation algorithms are used. Along with this classification, techniques are used for identifying the disease. The proposed algorithms' results are compared with those of standard state-of-the-art techniques.]]>
Copyrights © 2023
