Feed Forward Neural Network Classification for INDIAN Krishna Kamod Rice

The Carrying out effective and sustainable agriculture product has become an important issue in recent years. Agricultural production has to keep up with an ever-increasing population. A key to this is the usage of modern techniques (for precision agriculture) to take advantage of the quality in the market. Classification of rice seeds from the bare human hands is neither cost effective nor recommended. The automatic grading for analysis of quality has become the need of the hour. This paper recommends an add-on approach to quality experts for the quality analysis of INDIAN Krishna Kamod Rice using computer vision and soft computing techniques. Computer Vision provides a grading methodology, nondestructive technique, along with multi-layer feed forward neural networking which achieves high degree of quality than human vision inspection.