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Proceedings Paper

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

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.

Paper Details

Date Published: 31 January 2020
PDF: 6 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114270L (31 January 2020); doi: 10.1117/12.2550346
Show Author Affiliations
Haiyang Hua, Shenyang Institute of Automation (China)
Institutes for Robotics and Intelligent Manufacturing (China)
Univ. of Chinese Academy of Sciences/Key Lab. of Opto-Electronic Information Processing (China)
Zelin Shi, Shenyang Institute of Automation (China)
Institutes for Robotics and Intelligent Manufacturing (China)
Key Lab. of Opto-Electronic Information Processing (China)
Yunpeng Liu, Shenyang Institute of Automation (China)
Institutes for Robotics and Intelligent Manufacturing (China)
Key Lab. of Opto-Electronic Information Processing (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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