基于 AP 聚类算法的图像分割应用与研究

摘要

Aiming at the problem that many conventional clustering algorithms have low reliability due to the fact that-they are very sensitive to the value which is selected for the initial clustering center,the affinity propagation clustering algo-rithm which avoids the difficulty of selecting initial cluster centers by generating high quality centers through the transmis-sion of messages between different data-points is used in this paper for image segmentation.By comparing with experimental results of image segmentation using K-means algorithm and fuzzy C-means algorithm individually,the present algorithm is superior to them and can get much better segmentation results.%针对传统聚类算法在图像分割中对聚类中心选择敏感，可靠性差的缺点，本文采用 AP 聚类算法研究图像分割问题。AP(Affinity propagation)聚类算法是通过数据点之间的信息传递产生高质量的聚类中心，避免了聚类初始中心选择难的问题。本文通过与 K 均值算法和模糊 C 均值算法在图像分割中的实验比较，得出本算法优于其他两种算法，对图像可取得良好的分割效果。