Forward Looking Infrared Target Matching Algorithm Based on Depth Learning and Matrix Double Transformation

DOI

10.2991/msmee-17.2017.279How to use a DOI?

Keywords

Infrared Image; Forward-Looking Image; Depth Learning; Target Matching; Feature Extraction

Abstract

Targeting at the human target detection in infrared sequence images, the extraction method of feature region based on feature points is adopted. The depth-learning algorithm is firstly used to extract the feature points rapidly. Based on the feature points extracted by matrix double transformation, LBP algorithm is used to extract the feature region. After acquiring the feature region (ROI region) interested, feature extraction of wavelet entropy based on discrete wavelet transformation is conducted for ROI region. Then ROI region is classified through compound classification method.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiongfei Wu
AU  - Yong ZHu
AU  - Yi Chen
AU  - Zhiqiang Zhang
PY  - 2017/05
DA  - 2017/05
TI  - Forward Looking Infrared Target Matching Algorithm Based on Depth Learning and Matrix Double Transformation
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 1551
EP  - 1556
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.279
DO  - 10.2991/msmee-17.2017.279
ID  - Wu2017/05
ER  -