摘要
DF__DBSCAN算法(An Improved DBSCAN Clustering Algorithm Based on Data Field)是一种将数据场和密度聚类结合的算法。文章将该算法应用于图像分割,通过与其他图像分割算法进行实验对比,表明算法在图像分割上的适应性;通过对图像进行多种形式的预处理,反映势函数中参数mi对聚类结果的影响。
DF_DBSCAN Algorithm(An Improved DBSCAN Clustering Algorithm Based on Data Field)is an algorithm which combines data field with density clustering.In this paper,the DF_DBSCAN algorithm is applied to the image segmentation,by comparing with other image segmentation algorithms to show the adaptability of the algorithm in image segmentation;by taking variable image preprocessing on original image to reflect the effect of the parameter mion the clustering result.
作者
杨静
YANG Jing(Taiyuan Normal University Network Center, Yuci 030010,China)
出处
《电脑与信息技术》
2017年第3期22-25,32,共5页
Computer and Information Technology
