A Linear Fitting Density Peaks Clustering Algorithm for Image Segmentation

作者：You Zhou, Tiantian Zhao, Yizhang Wang, Jianan Wu, Xu Zhou · 发表于：Tehnicki vjesnik - Technical Gazette · 年份：2018 · DOI：10.17559/tv-20171125161944 · 被引用次数：8 · 研究领域：Image Retrieval and Classification Techniques、Medical Image Segmentation Techniques、Face and Expression Recognition

Clustering by fast search and finding of density peaks algorithm (DPC) is a recently developed method and can obtain promising results. However, DPC needs users to determine the number of clusters in advance, thus the clustering results are unstable and deeply influenced by the number of clusters. To address this issue, we proposed a novel algorithm, namely LDPC (Linear fitting Density Peaks Clustering algorithm). LDPC uses a novel linear fitting method to choose cluster centres automatically. In the experiments, we use public datasets to access the effectiveness of LDPC. Especially, we applied LDPC to image segmentation tasks. The experimental results show that LDPC can obtain competitive results compared with other clustering algorithms.