Classification of Wheat Grains Using Machine Algorithms

Meesha Punn, Nidhi Bhalla

Abstract: India is the second largest producer of wheat in the world after China. Specifying the quality of wheat manually requires an expert judgment and is time consuming. To overcome this problem, machine algorithms can be used to classify wheat according to its quality. In this paper we have done wheat classification by using two machine learning algorithms, that is, Support Vector Machine (OVR) and Neural Network (LM). For classification, images of wheat grain are captured using digital camera and thresholding is performed. Following this step, features of wheat are extracted from these images and machine learning algorithms are implemented. The accuracy of Support Vector Machine is 86.8 % and of Neural network is 94.5 %. Results show that Neural Network (LM) is better than Support Vector Machine (OVR).

Keywords: Classification, Computer Vision System, Image Processing, Grading, Quality, SVM, Wheat