Conditional based Edge Detection Algorithm Enhancing the Quality of Clustered Grain Seeds

In this study, we proposed a method of improving the edge detection of clustered grains (soybean seeds) to identify the actual shape of grain seeds and enhance the edge of seeds with the help of a conditional Sobel operator based edge. We designed methods that improve the edges of clustered soybean seeds from a digital image captured under non-ideal conditions. This is not mandatory, but results will be more reliable if that condition is observed. Basically, we compared some parameter that is energy, mean, median and range of image with respective base paper.