| Abstrakt: |
Now days the impact of climate change in India are mostly affected to the agriculture field, most of the agricultural crops are being badly affected in terms of their performance of the crop. The crop yield is used to predict in advance because of its harvest, its help the farmers for taking good decisions in marketing. The results of knowing crop yield and building prototype for the purpose of easily available to the farmer. Thus, for such kind of data analysis in the crop, there are different techniques and algorithms to predict the crop in a field. In this we have used image processing algorithm. The data used are images are taken from the drone system. Our approach starts by seeing rows inside the area (or acre) and finding all the trees in a crop yield, by this knowing the size of plant in the crop can be easily to store the data of plants. Lately there has been a wide source of spatial photogrammetry available for agriculture. Most of this data gives new information about the crops. By analysis of crop statics and methods have not been widely performed due to limitations on the images and software involved. The classification was also validated by comparing dozens of trees in the field, with excellent results. The purpose of this paper is to provide farmers with a method for quickly and automatically classifying trees by size, regardless of the presence or absence of problems, so that they can more easily monitor the health of individual trees and gain a better grasp on how those trees are distributed across a given area. [ABSTRACT FROM AUTHOR] |
