Body-surface trauma image segmentation

Image segmentation is highly concerned at all times, but body-surface trauma images segmentation is seldom reported. In this paper, regard to the features of body-surface trauma images, two kinds of procedures are designed for the segmentation of body-surface trauma images. For the images that have acute contrast in colors between the trauma part and the background, a procedure is proposed that has four steps based on the image segmentation techniques: image enhancing, color adjusting, RGB heft extracting, mathematical morphology processing are implemented according to the set sequence. As for gray-average images, another method that has seven steps based on Snakes model is put forward. These steps in turn are image enhancing, image graying, median filter, edge smoothing, initial contour extraction, snakes model iteration with different parameters, and B sample imitation. Experiments with real body-surface trauma images are presented. The results show the effectiveness of this method. The results of segment images provide preparative work for the quantitative analysis of trauma parameters with rapidity and accuracy.