A Blur-Invariant Local Feature for Motion Blurred Image Matching

被引:0
|
作者
Tong, Qiang [1 ]
Aoki, Terumasa [1 ,2 ]
机构
[1] Tohoku Univ, GSIS, Sendai, Miyagi, Japan
[2] Tohoku Univ, BNew Ind Creat Hatchery Ctr NICHe, Sendai, Miyagi, Japan
来源
NINTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2017) | 2017年 / 10420卷
关键词
local feature; blur-invariant; descriptor; moment; image matching;
D O I
10.1117/12.2281710
中图分类号
TB8 [摄影技术];
学科分类号
0804 ;
摘要
Image matching between a blurred (caused by camera motion, out of focus, etc.) image and a non-blurred image is a critical task for many image/video applications. However, most of the existing local feature schemes fail to achieve this work. This paper presents a blur-invariant descriptor and a novel local feature scheme including the descriptor and the interest point detector based on moment symmetry - the authors' previous work. The descriptor is based on a new concept - center peak moment-like element (CPME) which is robust to blur and boundary effect. Then by constructing CPMEs, the descriptor is also distinctive and suitable for image matching. Experimental results show our scheme outperforms state of the art methods for blurred image matching.
引用
收藏
页数:6
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