Application of K-means Algorithm in Image Compression

2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering

无线电电子学;计算机科学;材料科学

Wan, Xing^1

Leshan Vocational and Technical College, Leshan, Sichuan

614000, China^1

关键词: Basic principles;    K-means;    Machine learning problem;    Tagged data;    Unlabeled data;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/563/5/052042/pdf
DOI  :  10.1088/1757-899X/563/5/052042

来源: IOP

【 摘 要 】

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.