The Study on Image Compression Using the Genetic Algorithm and Segmentation Using the K-merging Algorithm

• Main Authors: Shen-I Yang, 楊紳誼
• Other Authors: Wen-Tsong Chen
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/60340870293520289545

碩士 === 立德大學 === 數位應用研究所 === 98 === The K-means algorithm had been widely applied to the study of image compression, in recently years, it is mainly used to design the codebook. In our study, a genetic algorithm is proposed to accomplish the purpose, with a parameter(w), controlling the clustering result in the algorithm. In our experiments, image compression base on the genetic algorithm outperforms that based on the K-means algorithm. The mean shift method had been applied to perform the image segmentation. Since the method segments the image based on pixels. The computation complexity is relatively high. In this study, we propose a K-merging method to segment the image based on blocks of image. The image segmentation based on K-merging method outperforms that based on the mean shift method in our study.