A Versatile Mobile Application for Quality Prediction of Wheat Grain using Machine Learning Algorithms

Abstract: Indian agriculture field is second largest producer of wheat after china which is major backbone to Indian economy. The new innovations can be applied to this field to get new products. Manually quality prediction of wheat grain is very tedious task and it is time consuming so an automated quality prediction system is developed using mobile application and various image processing techniques. The objective of this is paper to accurately predict the quality of wheat grain without any intermediate person. Finding the quality of wheat grain is performed in MATLAB using various machine learning algorithms. Through mobile application wheat grain image is sent to server for identifying its quality. Server processes and classifies the image using various machine learning algorithms like SVM and K nearest neighbor and sends back result to mobile application which contains the quality/purity level of wheat grain and based on quality also gives the price for grain.

Keywords: Image Processing, Mobile Application, SVM, KNN.