TY - GEN
T1 - UAV-based multispectral aerial image retrieval using spectral feature and semantic computing
AU - Wijitdechakul, Jinmika
AU - Sasaki, Shiori
AU - Kiyoki, Yasushi
AU - Koopipat, Chawan
N1 - Funding Information:
This research is supported in part by Ministry of Education, Culture, Sports, Science and Technology (MEXT) Grant-in-Aid for the program for leading graduate school program: Global Environmental System Leaders (GESL), Keio SFC Academic Society (Keio Shonan Fujisawa Gakkai) and Multimedia Database Laboratory (MDBL), Graduate School of Media and Governance, Keio University. We also express gratitude to the anonymous reviewers for their valuable comment and suggestion.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - This research proposes the multispectral image retrieval method by using spectral feature and semantic computing which is not many studies have focused. The main contributions are to enhance the effectiveness and advantageous of global environmental analysis system and realize semantic associative search and analysis. In this work, we study multispectral image retrieval using spectral feature computed in multispectral semantic-image space. The multispectral semantic-image space is supposing to realize the interpretation of substance (materials) on earth surface which can be provided the analyzed results as human-level interpretation. Our essential approach is utilizing the semantic computing to measure the similarity between multispectral image and the meaningful keywords which according to the user's contexts. Our research results found that this method possible to acquire the spectral feature from the multispectral image and could be used in multispectral image retrieval. In this study, a multispectral image is used as the image query according to user's query contexts. Moreover, the method performance of UAV-based multispectral aerial image retrieval using spectral feature and semantic computing is measured based on the queries with three contexts of multispectral image which is indicated by previous study on agricultural monitoring system and semantic interpretation model.
AB - This research proposes the multispectral image retrieval method by using spectral feature and semantic computing which is not many studies have focused. The main contributions are to enhance the effectiveness and advantageous of global environmental analysis system and realize semantic associative search and analysis. In this work, we study multispectral image retrieval using spectral feature computed in multispectral semantic-image space. The multispectral semantic-image space is supposing to realize the interpretation of substance (materials) on earth surface which can be provided the analyzed results as human-level interpretation. Our essential approach is utilizing the semantic computing to measure the similarity between multispectral image and the meaningful keywords which according to the user's contexts. Our research results found that this method possible to acquire the spectral feature from the multispectral image and could be used in multispectral image retrieval. In this study, a multispectral image is used as the image query according to user's query contexts. Moreover, the method performance of UAV-based multispectral aerial image retrieval using spectral feature and semantic computing is measured based on the queries with three contexts of multispectral image which is indicated by previous study on agricultural monitoring system and semantic interpretation model.
KW - Agricultural Monitoring System
KW - Semantic computing
KW - UAV-based multispectral Image
KW - multispectral image retrieval
UR - http://www.scopus.com/inward/record.url?scp=85046543076&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046543076&partnerID=8YFLogxK
U2 - 10.1109/KCIC.2017.8228571
DO - 10.1109/KCIC.2017.8228571
M3 - Conference contribution
AN - SCOPUS:85046543076
T3 - Proceedings - International Electronics Symposium on Knowledge Creation and Intelligent Computing, IES-KCIC 2017
SP - 101
EP - 107
BT - Proceedings - International Electronics Symposium on Knowledge Creation and Intelligent Computing, IES-KCIC 2017
A2 - Bagar, Fahim Nur Cahya
A2 - Zainudin, Ahmad
A2 - Al Rasyid, M. Udin Harun
A2 - Briantoro, Hendy
A2 - Akbar, Zulhaydar Fairozal
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Electronics Symposium on Knowledge Creation and Intelligent Computing, IES-KCIC 2017
Y2 - 26 September 2017 through 27 September 2017
ER -