A new method of subway tunnel crack image compression based on roi and motion estimation

被引：0
|
作者：
Department of Electronic and Information Engineering, Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing Jiaotong University, Beijing [1 ]
100044, China
不详 [2 ]
100044, China
机构：
来源：
J. Comput. | / 3卷 / 20-28期
关键词：
Cracks - Discrete cosine transforms - Image coding - Image enhancement - Railroads - Image segmentation - Motion estimation;
D O I：
暂无
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
Aiming at the characteristics of the subway tunnel crack images, this paper presents a new method of subway tunnel crack image compression based on region of interest and motion estimation. It contains three key parts: the method of key frame image compression based on Discrete Cosine Transformation, the method of internal frame image compression based on forward predictive coding and motion estimation, the method of lossless image compression based on crack information database and suspected crack regions. The simulation experiment results show that this method can not only enhance the image compression ratio without losing any information of images in the region of interest, but also interface with the existing subway tunnel crack recognition system very well and make good use of the data from the crack recognition system database and the images in the disk array.
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