A metric based on saliency line feature extraction and connection for matching area selection

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 光电信息技术研究室

	A metric based on saliency line feature extraction and connection for matching area selection
	Hua HY(花海洋)1,2,3,4; Shi ZL(史泽林)2,3,4; Liu YP(刘云鹏)2,3,4
	2019
会议日期	August 28-30, 2019
会议地点	Shenyang, China
关键词	Vision navigation suitable matching area saliency line feature monogenic phase congruency convex shape descriptor
页码	1-6
英文摘要	Selecting a reliability matching area as template is one of the key issues to vision navigation. This paper proposes a metric for matching area selection based on line feature extraction and connection. Firstly, a new line feature is introduced to approximate the reliability information about matching area, which is called saliency line feature. Then, extracting method of these line features is put forward based on monogenic phase congruency model. Secondly, a convex shape descriptor is proposed to represent the spatial distribution characteristic of the line features by connection. Finally, a measure method is defined by merging the quantity and spatial distribution characteristic of the saliency line features, which can guide to select better matching area. The experimental results show that the proposed metric is valid and effective.
源文献作者	Chinese Society for Optical Engineering
产权排序	1
会议录	Second Target Recognition and Artificial Intelligence Summit Forum
会议录出版者	SPIE
会议录出版地	Bellingham, USA
语种	英语
ISSN号	0277-786X
ISBN号	978-1-5106-3631-6
WOS记录号	WOS:000546230500020
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26415]
专题	沈阳自动化研究所_光电信息技术研究室
通讯作者	Hua HY(花海洋)
作者单位	1.University of Chinese Academy of Sciences, Beijing, China 2.Key Laboratory of Opto-Electronic Information Processing CAS, Shenyang, China 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110069, China
推荐引用方式 GB/T 7714	Hua HY,Shi ZL,Liu YP. A metric based on saliency line feature extraction and connection for matching area selection[C]. 见:. Shenyang, China. August 28-30, 2019.