A Regenerated Feature Extraction Method for Cross-modal Image Registration

Jian Yang, Qi Wang, Xuelong Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Cross-modal image registration is an intractable problem in computer vision and pattern recognition. Inspired by that human gradually deepen to learn in the cognitive process, we present a novel method to automatically register images with different modes in this paper. Unlike most existing registrations that align images by single type of features or directly using multiple features, we employ the “regenerated” mechanism cooperated with a dynamic routing to adaptively detect features and match for different modal images. The geometry-based maximally stable extremal regions (MSER) are first implemented to fast detect non-overlapping regions as the primitive of feature regeneration, which are used to generate novel control-points using salient image disks (SIDs) operator embedded by a sub-pixel iteration. Then a dynamic routing is proposed to select suitable features and match images. Experimental results on optical and multi-sensor images show that our method has a better accuracy compared to state-of-the-art approaches.

源语言英语
主期刊名Advances in Brain Inspired Cognitive Systems - 9th International Conference, BICS 2018, Proceedings
编辑Amir Hussain, Bin Luo, Jiangbin Zheng, Xinbo Zhao, Cheng-Lin Liu, Jinchang Ren, Huimin Zhao
出版商Springer Verlag
441-451
页数11
ISBN(印刷版)9783030005627
DOI
出版状态已出版 - 2018
活动9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018 - Xi'an, 中国
期限: 7 7月 20188 7月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10989 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议9th International Conference on Brain-Inspired Cognitive Systems, BICS 2018
国家/地区中国
Xi'an
时期7/07/188/07/18

指纹

探究 'A Regenerated Feature Extraction Method for Cross-modal Image Registration' 的科研主题。它们共同构成独一无二的指纹。

引用此