Quality Testing and Grading of Food Grains Using Digital Image Processing

Food grains are the farming product which require the supervision to identify the quality. This quality estimation will help in audit system as well as to protect it from insect infection. But a false report or a wrong sampled based observation can completely fails this analysis process. These situations occurs because of lack of availability of such quality measure labs in near region. In this paper, different digital image processing steps such as gray scale conversion ,segmentation, morphological feature extraction and training and testing through feed forward propagation algorithm and k-mean clustering are used and find out the best algorithm for quality analysis of food grains.