Apple image segmentation based on the minimum error Bayes decision

To accomplish the goal of completely automatic apple grading, the segmentation ways of apple image were analyzed. Based on the minimum error Bayes decision theory, the authors proposed a new way of image segmentation. Various parameters obeying normal distribution were estimated from the histogram and the pixels were judged to different sorts. Good segmentation results were obtained from several testing images. The results demonstrate that this method does not require any filter and has better ability in restraining interference. It is a feasible way for image segmentation.