Application of K-means Algorithm in Image Compression
Xing Yu Wan · IOP Conference Series Materials Science and Engineering · 2019
Abstract In machine learning problems, there are two main algorithms: supervised learning and unsupervised learning. Supervised learning algorithms can be used to classify data for tagged data; non-supervised learning algorithms can be used to cluster data for unlabeled data. This paper discusses the basic principles of clustering algorithm and selection of key parameters of clustering algorithm. The application of clustering algorithm in image compression is also analyzed. This paper also emphasizes the problems that should be paid attention to when using clustering. Finally, a practical case of image compression with K-means is given.