An image segmentation method based on 3-D threshold and predator-prey particle swarm optimization

A new method of image segmentation based on 3-D Otsu threshold is proposed. The method not only retains the traditional 2-D Otsu methods advantages, but also makes full use of the fuzzy information of the image-fuzzy median value, which with gray value and gray mean value constitute a 3-D feature vector. Based on the complementation, competition and redundancy of all information, this algorithm improves the accuracy of segmentation. In addition, predator prey particle swarm optimization (PPPSO) is used to search for the best threshold, which can reduce the search time greatly and converge to global optimum rapidly. Theoretical analysis and experiment results show that this method has a good anti-noise and real-time performance. © 2012 by Binary Information Press.