Detection of plant diseases using image-based similarity measures of Pythagorean fuzzy sets

Abstract

In image processing, data extraction from any image with deviation is difficult to pursue. Especially in identification of radiological images, many issues have been involved in the choosing of right image from the available images. In this paper, new similarity measure model for images is proposed that have application in the identification of the images of plant diseases. The application of the similarity measures is compared with existing models. The results reports that the proposed Pythagorean entropy measures have application in the detection of plant diseases. Even, the quality ofextraction of data from images is enhanced. Further, the study concludes that the proposed measures are better than the existing measures in case of image processing problems.